@inproceedings{schubert16icra,
  author = {Tobias Schubert and Katharina Eggensperger and Alexis Gkogkidis and Frank Hutter and Tonio Ball and Wolfram Burgard},
  title = {Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2016,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/schubert16icra.pdf},
  address = {Stockholm, Sweden}
}
@inproceedings{oliveira2016,
  author = {Gabriel Oliveira and Abhinav Valada and Claas Bollen and Wolfram Burgard and Thomas Brox},
  title = {Deep Learning for Human Part Discovery in Images},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year = 2016,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/oliveira16icra.pdf},
  address = {Stockholm, Sweden}
}
@inproceedings{dewan16icra,
  author = {Ayush Dewan and Tim Caselitz and Gian Diego Tipaldi and Wolfram Burgard},
  title = {Motion-based Detection and Tracking in 3D LiDAR Scans},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2016,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/dewan16icra.pdf},
  address = {Stockholm, Sweden}
}
@inproceedings{radwan16icra,
  author = {Noha Radwan and Gian Diego Tipaldi and Luciano Spinello and Wolfram Burgard},
  title = {Do you see the Bakery? Leveraging Geo-Referenced Texts for Global Localization in Public Maps},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2016,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/radwan16icra.pdf},
  address = {Stockholm, Sweden}
}
@inproceedings{boniardi16icra,
  author = {Federico Boniardi and Abhinav Valada and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Autonomous Indoor Robot Navigation Using a Sketch Interface for Drawing Maps and Routes},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2016,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/boniardi16icra.pdf},
  address = {Stockholm, Sweden}
}
@article{osswald16ral,
  author = {Stefan O{\ss}wald and Maren Bennewitz and Wolfram Burgard and Cyrill Stachniss},
  title = {Speeding-Up Robot Exploration by Exploiting Background Information},
  journal = {{IEEE} Robotics and Automation Letters (RA-L)},
  volume = {1},
  number = {2},
  pages = {716--723},
  year = 2016,
  doi = {10.1109/LRA.2016.2520560},
  issn = {2377-3766}
}
@article{sprunk16auro,
  author = {Christoph Sprunk and Boris Lau and Patrick Pfaff and Wolfram Burgard},
  title = {An Accurate and Efficient Navigation System for Omnidirectional Robots in Industrial Environments},
  journal = {Autonomous Robots},
  pages = {1--21},
  year = 2016,
  doi = {10.1007/s10514-016-9557-1},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sprunk16auro.pdf},
  issn = {1573-7527}
}
@article{kretzschmar16ijrr,
  author = {Henrik Kretzschmar and Markus Spies and Christoph Sprunk and Wolfram Burgard},
  title = {Socially Compliant Mobile Robot Navigation via Inverse Reinforcement Learning},
  journal = {The International Journal of Robotics Research},
  year = 2016,
  doi = {10.1177/0278364915619772},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kretzschmar16ijrr.pdf}
}
@phdthesis{sprunk15phd,
  author = {Christoph Sprunk},
  title = {Highly Accurate Mobile Robot Navigation},
  school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
  year = 2015,
  month = nov,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sprunk15phd.pdf}
}
@phdthesis{agarwal15phd,
  author = {Pratik Agarwal},
  title = {Robust Graph-Based Localization and Mapping},
  school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
  year = 2015,
  month = apr,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal15phd.pdf}
}
@inproceedings{eitel15iros,
  author = {Andreas Eitel and Jost Tobias Springenberg and Luciano Spinello and Martin Riedmiller and Wolfram Burgard},
  title = {Multimodal Deep Learning for Robust RGB-D Object Recognition},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Intelligent Robots and Systems (IROS)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/eitel15iros.pdf},
  address = {Hamburg, Germany}
}
@inproceedings{agarwal15iros,
  author = {Pratik Agarwal and Wolfram Burgard and Luciano Spinello},
  title = {Metric Localization using Google Street View},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Intelligent Robots and Systems (IROS)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal15iros.pdf},
  address = {Hamburg, Germany}
}
@inproceedings{behzadian15iros,
  author = {Bahram Behzadian and Pratik Agarwal and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Monte Carlo Localization in Hand-Drawn Maps},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Intelligent Robots and Systems (IROS)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/behzadian15iros.pdf},
  address = {Hamburg, Germany}
}
@inproceedings{wachaja15iros,
  author = {Wachaja, Andreas and Agarwal, Pratik and Zink, Mathias and Reyes Adame, Miguel and M\"oller, Knut and Burgard, Wolfram},
  title = {Navigating Blind People with a Smart Walker},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Intelligent Robots and Systems (IROS)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wachaja15iros.pdf},
  address = {Hamburg, Germany}
}
@inproceedings{naseer15iros,
  author = {Naseer, Tayyab and Ruhnke, Michael and Spinello, Luciano and Stachniss, Cyrill and Burgard, Wolfram},
  title = {Robust Visual SLAM Across Seasons},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Intelligent Robots and Systems (IROS)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/naseer15iros.pdf}
}
@inproceedings{roewekaemper15iros,
  author = {J\"org R\"owek\"amper and Benjamin Suger and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Accurate Localization with Respect to Moving Objects via Multiple-Body Registration},
  booktitle = {Proc.~of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/roewekaemper15iros.pdf}
}
@inproceedings{mazuran15isrr,
  author = {Mladen Mazuran and Federico Boniardi and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Relative Topometric Localization in Globally Inconsistent Maps},
  booktitle = {Proc.~of the International Symposium on Robotics Research (ISRR)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mazuran15isrr.pdf},
  address = {Sestri Levante}
}
@inproceedings{valada15isrr,
  author = {Abhinav Valada and Luciano Spinello and Wolfram Burgard},
  title = {Deep Feature Learning for Acoustic-based Terrain Classification},
  booktitle = {Proc.~of the International Symposium on Robotics Research (ISRR)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/valada15isrr.pdf},
  address = {Sestri Levante}
}
@inbook{burgard15worldrobotics,
  author = {Wolfram Burgard and Patrick Pfaff and Christoph Sprunk},
  title = {World Robotics 2015 Service Robots: Statistics, Market Analysis, Forecasts, Case Studies},
  pages = {256--263},
  year = 2015,
  chapter = {Flexible Autonomous Navigation for Industrial Shop
                   Floor Applications},
  publisher = {International Federation of Robotics (IFR),
                   Statistical Department},
  isbn = {978-3-8163-0680-1},
  editor = {Martin H\"agele}
}
@inproceedings{kollmitz15ecmr,
  author = {Marina Kollmitz and Kaijen Hsiao and Johannes Gaa and Wolfram Burgard},
  title = {Time Dependent Planning on a Layered Social Cost Map for Human-Aware Robot Navigation},
  booktitle = {Proc.~of the IEEE European Conference on Mobile Robots (ECMR)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kollmitz15ecmr.pdf},
  address = {Lincoln}
}
@inproceedings{boniardi15ecmr,
  author = {Federico Boniardi and Bahram Behzadian and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Robot Navigation in Hand-Drawn Sketched Maps},
  booktitle = {Proc.~of the IEEE European Conference on Mobile Robots (ECMR)},
  year = 2015,
  doi = {10.1109/ECMR.2015.7324188},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/boniardi15ecmr.pdf},
  address = {Lincoln}
}
@inproceedings{dilucia15ecmr,
  author = {Stefano {Di~Lucia} and Gian Diego Tipaldi and Wolfram Burgard},
  title = {Attitude Stabilization Control of an Aerial Manipulator using a Quaternion-based Backstepping Approach},
  booktitle = {Proc.~of the IEEE European Conference on Mobile Robots (ECMR)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/dilucia15ecmr.pdf},
  address = {Lincoln}
}
@inproceedings{naseer15ecmr,
  author = {Naseer, Tayyab and Suger, Benjamin and Ruhnke, Michael and Burgard, Wolfram},
  title = {Vision-Based Markov Localization Across Large Perceptual Changes},
  booktitle = {Proc.~of the IEEE European Conference on Mobile Robots (ECMR)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/naseer15ecmr.pdf},
  address = {Lincoln}
}
@inproceedings{mazuran15icra,
  author = {Mladen Mazuran and Christoph Sprunk and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Lex{TOR}: Lexicographic Teach Optimize and Repeat Based on User Preferences},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mazuran15icra.pdf},
  address = {Seattle}
}
@inproceedings{schroeer15icra,
  author = {S. Schr\"oer and I. Killmann and B. Frank and M. V\"olker and L. D. J. Fiederer and T. Ball and W. Burgard},
  title = {An Autonomous Robotic Assistant for Drinking},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/schroeer15icra.pdf}
}
@inproceedings{schubert15icra,
  author = {Tobias Schubert and Alexis Gkogkidis and Tonio Ball and Wolfram Burgard},
  title = {Automatic Initialization for Skeleton Tracking in Optical Motion Capture},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  pages = {734--739},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/schubert15icra.pdf}
}
@inproceedings{frank15icra,
  author = {B. Frank and M. Ruhnke and M. Tatarchenko and W. Burgard},
  title = {{3D}-Reconstruction of Indoor Environments from Human Activity},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank15icra.pdf}
}
@inproceedings{roewekaemper15icra,
  author = {J\"org R\"owek\"amper and Michael Ruhnke and Bastian Steder and Wolfram Burgard and Gian Diego Tipaldi},
  title = {Automatic Extrinsic Calibration of Multiple Laser Range Sensors with Little Overlap},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/roewekaemper15icra.pdf}
}
@inproceedings{ruchti15icra,
  author = {Philipp Ruchti and Bastian Steder and Michael Ruhnke and Wolfram Burgard},
  title = {Localization on OpenStreetMap Data using a 3D Laser Scanner},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruchti15icra.pdf}
}
@inproceedings{suger15icra,
  author = {Benjamin Suger and Bastian Steder and Wolfram Burgard},
  title = {Traversability Analysis for Mobile Robots in Outdoor Environments: A Semi-Supervised Learning Approach Based on 3D-Lidar Data},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/suger15icra.pdf}
}
@inproceedings{steder15icra,
  author = {Bastian Steder and Michael Ruhnke and Rainer K{\"u}mmerle and Wolfram Burgard},
  title = {Maximum Likelihood Remission Calibration for Groups of Heterogeneous Laser Scanners},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder15icra.pdf}
}
@inproceedings{kuderer15icra,
  author = {Markus Kuderer and Shilpa Gulati and Wolfram Burgard},
  title = {Learning Driving Styles for Autonomous Vehicles from Demonstration},
  booktitle = {Proc.~of the IEEE International Conference on Robotics and Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuderer15icra.pdf},
  address = {Seattle, USA}
}
@inproceedings{abdo15icra,
  author = {Nichola Abdo and Cyrill Stachniss and Luciano Spinello and Wolfram Burgard},
  title = {Robot, Organize my Shelves! Tidying up Objects by Predicting User Preferences},
  booktitle = {Proc.~of the IEEE International Conference on Robotics and Automation (ICRA)},
  year = 2015,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/abdo15icra.pdf},
  address = {Seattle, USA}
}
@incollection{sprunk14iser,
  author = {C. Sprunk and J. Roewekaemper and G. Parent and L. Spinello and G. D. Tipaldi and W. Burgard and M. Jalobeanu},
  title = {An Experimental Protocol for Benchmarking Robotic Indoor Navigation},
  booktitle = {Experimental Robotics},
  volume = {109},
  pages = {487--504},
  year = 2015,
  doi = {10.1007/978-3-319-23778-7_32},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sprunk14iser.pdf},
  publisher = {Springer International Publishing},
  isbn = {978-3-319-23777-0},
  editor = {Hsieh, M. Ani and Khatib, Oussama and Kumar,
                   Vijay},
  series = {Springer Tracts in Advanced Robotics}
}
@article{kummerle14jfr,
  author = {K{\"u}mmerle, Rainer and Ruhnke, Michael and Steder, Bastian and Stachniss, Cyrill and Burgard, Wolfram},
  title = {Autonomous Robot Navigation in Highly Populated Pedestrian Zones},
  journal = {Journal of Field Robotics},
  year = 2014,
  doi = {10.1002/rob.21534},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle14jfr.pdf}
}
@article{endres14tro,
  author = {F. Endres and J. Hess and J. Sturm and D. Cremers and W. Burgard},
  title = {3{D} Mapping with an {RGB-D} Camera},
  journal = {IEEE Trans. on Robotics},
  volume = {30},
  number = {1},
  pages = {177--187},
  year = 2014,
  month = feb,
  doi = {10.1109/TRO.2013.2279412},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres14tro.pdf}
}
@inproceedings{endres14iros,
  author = {F. Endres and C. Sprunk and R. K{\"u}mmerle and W. Burgard},
  title = {A Catadioptric Extension for {RGB-D} Cameras},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2014,
  doi = {10.1109/IROS.2014.6942600},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres14iros.pdf},
  location = {Chicago, Illinois, USA}
}
@inproceedings{vysotska14iros,
  author = {O. Vysotska and B. Frank and I. Ulbert and O. Paul and P. Ruther and C. Stachniss and W. Burgard},
  title = {Automatic Channel Selection and Neural Signal Estimation across Channels of Neural Probes},
  booktitle = {Proceedings of the {IEEE/RSJ} International
Conference on Intelligent
Robots and Systems ({IROS})},
  pages = {1453-1459},
  year = 2014,
  month = sep,
  doi = {10.1109/IROS.2014.6942748},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/vysotska14iros.pdf},
  keyword = {Neurorobotics, Brain Machine Interfaces},
  address = {Chicago, IL, USA}
}
@inproceedings{wachaja14iros-ws,
  author = {Andreas Wachaja and Pratik Agarwal and Miguel Reyes Adame and Knut M\"oller and Wolfram Burgard},
  title = {A Navigation Aid for Blind People with Walking Disabilities},
  booktitle = {IROS Workshop on Rehabilitation and Assistive Robotics: Bridging the Gap Between Clinicians and Roboticists},
  year = 2014,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wachaja14iros-ws.pdf},
  address = {Chicago, USA}
}
@article{agarwal14ram,
  author = {Pratik Agarwal and Wolfram Burgard and Cyrill Stachniss},
  title = {A Survey of Geodetic Approaches to Mapping and
the Relationship to Graph-Based SLAM},
  journal = {Robotics and Automation Magazine},
  year = 2014,
  month = sep,
  doi = {10.1109/MRA.2014.2322282},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal-geodetic.pdf}
}
@inproceedings{agarwal14icra-dcs,
  author = {Pratik Agarwal and Giorgio Grisetti and Gian Diego Tipaldi and Luciano Spinello and Wolfram Burgard and Cyrill Stachniss},
  title = {Experimental Analysis of Dynamic Covariance
Scaling for Robust Map Optimization Under Bad
Initial Estimates},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation ({ICRA})},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907383},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal2014bicra.pdf},
  keyword = {SLAM, Robust optimization},
  address = {Hong Kong, China}
}
@inproceedings{agarwal14icra-geo,
  author = {Pratik Agarwal and Wolfram Burgard and Cyrill Stachniss},
  title = {Helmert's and Bowie's Geodetic Mapping Methods
and Their Relationship to Graph-Based SLAM},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation ({ICRA})},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907382},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal2014aicra.pdf},
  keyword = {SLAM, Survey, Geodetic},
  address = {Hong Kong, China}
}
@inproceedings{beinhofer14arw,
  author = {Maximilian Beinhofer and Wolfram Burgard},
  title = {Efficient Estimation of Expected Distributions
for Mobile Robot Navigation},
  booktitle = {Proc.~of the Austrian Robotics Workshop (ARW)},
  year = 2014,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beinhofer14arw.pdf},
  address = {Linz, Austria}
}
@phdthesis{joho14diss,
  author = {Dominik Joho},
  title = {Learning and Utilizing Spatial Object Relations
for Service Robots},
  school = {Albert-Ludwigs-Universit\"{a}t Freiburg},
  year = 2014,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho14diss.pdf}
}
@inproceedings{kuderer14icsr,
  author = {Markus Kuderer and Wolfram Burgard},
  title = {An Approach to Socially Compliant Leader Following for Mobile Robots},
  booktitle = {Social Robotics},
  volume = {8755},
  pages = {239-248},
  year = 2014,
  doi = {10.1007/978-3-319-11973-1_24},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuderer14icsr.pdf},
  publisher = {Springer International Publishing},
  series = {Lecture Notes in Computer Science}
}
@inproceedings{kretzschmar14icra,
  author = {Henrik Kretzschmar and Markus Kuderer and Wolfram Burgard},
  title = {Learning to Predict Trajectories of
Cooperatively Navigating Agents},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907442},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kretzschmar14icra.pdf},
  address = {Hong Kong, China}
}
@inproceedings{kuderer14icra,
  author = {Markus Kuderer and Christoph Sprunk and Henrik Kretzschmar and Wolfram Burgard},
  title = {Online Generation of Homotopically Distinct
Navigation Paths},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907813},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuderer14icra.pdf},
  address = {Hong Kong, China}
}
@inproceedings{osswald14icra,
  author = {Stefan O{\ss}wald and Henrik Kretzschmar and Wolfram Burgard and Cyrill Stachniss},
  title = {Learning to Give Route Directions from Human Demonstrations},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  pages = {3303-3308},
  year = 2014,
  month = may,
  doi = {10.1109/ICRA.2014.6907334},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/osswald14icra.pdf},
  address = {Hong Kong, China},
  abstract = {For several applications, robots and other
                   computer systems must provide route descriptions to
                   humans. These descriptions should be natural and
                   intuitive for the human users. In this paper, we
                   present an algorithm that learns how to provide
                   good route descriptions from a corpus of human-
                   written directions. Using inverse reinforcement
                   learning, our algorithm learns how to select the
                   information for the description depending on the
                   context of the route segment. The algorithm then
                   uses the learned policy to generate directions that
                   imitate the style of the descriptions provided by
                   humans, thus taking into account personal as well
                   as cultural preferences and special requirements of
                   the particular user group providing the learning
                   demonstrations. We evaluate our approach in a user
                   study and show that the directions generated by our
                   policy sound similar to human-given directions and
                   substantially more natural than directions provided
                   by commercial web services.}
}
@article{wurm14ras,
  author = {Kai M. Wurm and Henrik Kretzschmar and Rainer K{\"u}mmerle and Cyrill Stachniss and Wolfram Burgard},
  title = {Identifying Vegetation from Laser Data in
Structured Outdoor Environments},
  journal = {Robotics and Autonomous Systems},
  volume = {62},
  pages = {675--684},
  year = 2014,
  doi = {10.1016/j.robot.2012.10.003},
  url = {http://www.sciencedirect.com/science/article/pii/S0921889012001868},
  issue = {5}
}
@inproceedings{ilg14icra,
  author = {Ilg, E. and K{\"u}mmerle, R. and Burgard, W. and Brox, T.},
  title = {Reconstruction of Rigid Body Models from Motion
Distorted Laser Range Data Using Optical Flow},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907535},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ilg14icra.pdf},
  address = {Hong Kong, China},
  abstract = {The setup of tilting a 2D laser range finder up
                   and down is a widespread strategy to acquire 3D
                   point clouds.  This setup requires that the scene
                   is static while the robot takes a 3D scan.  If an
                   object moves through the scene during the
                   measurement process and one does not take into
                   account these movements, the resulting model will
                   get distorted.  This paper presents an approach to
                   reconstruct the 3D model of a moving rigid object
                   from the inconsistent set of 2D measurements by the
                   help of a camera.  Our approach utilizes optical
                   flow in the camera images to estimate the motion in
                   the image plane and point-line constraints to
                   compensate the missing information about the motion
                   in depth.  We combine multiple sweeps and/or views
                   into to a single consistent model using a point-to-
                   plane ICP approach and optimize single sweeps by
                   smoothing the resulting trajectory.  Experiments
                   obtained in real outdoor scenarios with moving cars
                   demonstrate that our approach yields accurate
                   models.}
}
@inproceedings{mazuran14rss,
  author = {Mladen Mazuran and Gian Diego Tipaldi and Luciano Spinello and Wolfram Burgard},
  title = {Nonlinear Graph Sparsification for SLAM},
  booktitle = {Proc.~of Robotics: Science and Systems (RSS)},
  year = 2014,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mazuran14rss.pdf},
  address = {Berkeley}
}
@inproceedings{mazuran14icra,
  author = {Mladen Mazuran and Gian Diego Tipaldi and Luciano Spinello and Wolfram Burgard and Cyrill Stachniss},
  title = {A Statistical Measure for Map Consistency in
SLAM},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907387},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mazuran14icra1.pdf},
  address = {Hong Kong}
}
@inproceedings{meyer14icra,
  author = {J. Meyer and M. Kuderer and J. M{\"u}ller and W. Burgard},
  title = {Online Marker Labeling for Fully Automatic
Skeleton Tracking in Optical Motion Caputure},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907690},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyer14icra.pdf}
}
@article{frank14ras,
  author = {B. Frank and C. Stachniss and R. Schmedding and M. Teschner and W. Burgard},
  title = {Learning object deformation models for robot
motion planning},
  journal = {Robotics and Autonomous Systems},
  volume = {62},
  number = {8},
  pages = {1153-1174},
  year = 2014,
  month = apr,
  doi = {10.1016/j.robot.2014.04.005},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank14ras.pdf}
}
@inproceedings{naseer14aaai,
  author = {T. Naseer and L. Spinello and W. Burgard and C. Stachniss},
  title = {Robust Visual Robot Localization Across Seasons
using Network Flows},
  booktitle = {Proc.~of the Conf.~of the  Association for the
Advancement of Artificial Intelligence (AAAI)},
  year = 2014,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/naseer14aaai.pdf},
  note = {In press},
  address = {Quebec, Canada}
}
@inproceedings{abdo14icra,
  author = {N. Abdo and L. Spinello and W. Burgard and C. Stachniss},
  title = {Inferring What to Imitate in Manipulation
Actions by Using a Recommender System},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907006},
  address = {Hong Kong, China}
}
@inproceedings{ito14icra,
  author = {S. Ito and F. Endres and M. Kuderer and G.D. Tipaldi and C. Stachniss and W. Burgard},
  title = {W-RGB-D: Floor-Plan-Based Indoor Global
Localization Using a Depth Camera and WiFi},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6906890},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ito14icra.pdf},
  address = {Hong Kong, China}
}
@inproceedings{suger14icra,
  author = {Benjamin Suger and Gian D. Tipaldi and  Luciano Spinello and W. Burgard},
  title = {An Approach to Solving Large-Scale SLAM
Problems with a Small Memory Footprint},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2014,
  doi = {10.1109/ICRA.2014.6907384},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/suger14icra.pdf}
}
@article{olson2013ijrr,
  author = {Edwin Olson and Pratik Agarwal},
  title = {Inference on networks of mixtures for robust
robot mapping},
  journal = {International Journal of Robotics Research},
  volume = {32},
  number = {7},
  pages = {826-840},
  year = 2013,
  month = jul,
  doi = {http://ijr.sagepub.com/content/32/7/826.abstract?etocv},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal2013ijrr.pdf}
}
@inproceedings{endres13icra-ws,
  author = {F. Endres and J. Trinkle and W. Burgard},
  title = {Interactive Perception for Learning the Dynamics of Articulated Objects},
  booktitle = {Proceedings of the ICRA 2013 Mobile Manipulation Workshop on Interactive Perception},
  year = 2013,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres13icra-ws.pdf},
  address = {Karlsruhe, Germany}
}
@inproceedings{agarwal13icra,
  author = {Pratik Agarwal and Gian Diego Tipaldi and Luciano Spinello and Cyrill Stachniss and Wolfram Burgard},
  title = {Robust Map Optimization using Dynamic
Covariance Scaling},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation ({ICRA})},
  year = 2013,
  month = may,
  doi = {10.1109/ICRA.2013.6630557},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwalicra13_DCS.pdf},
  keyword = {SLAM, Robust optimization},
  address = {Karlsruhe, Germany}
}
@inproceedings{agarwal13icraws,
  author = {Pratik Agarwal and Gian Diego Tipaldi and Luciano Spinello and Cyrill Stachniss and Wolfram Burgard},
  title = {Dynamic Covariance Scaling for Robust Robotic
Mapping},
  booktitle = {Workshop on robust and Multimodal Inference in
Factor Graphs, {ICRA}},
  year = 2013,
  month = may,
  doi = {10.1109/ICRA.2013.6630557},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/agarwal13_icra_ws.pdf},
  keyword = {SLAM, Robust optimization},
  address = {Karlsruhe, Germany}
}
@inproceedings{endres13iros,
  author = {F. Endres and J. Trinkle and W. Burgard},
  title = {Learning the Dynamics of Doors for Robotic Manipulation},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent Robots and Systems (IROS)},
  year = 2013,
  month = nov,
  doi = {10.1109/IROS.2013.6696861},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres13iros.pdf},
  address = {Tokyo, Japan}
}
@inproceedings{beinhofer13iros,
  author = {Maximilian Beinhofer and J{\"o}rg M{\"u}ller and Andreas Krause and Wolfram Burgard},
  title = {Robust Landmark Selection for Mobile Robot
Navigation},
  booktitle = {Proc.~of the IEEE Int. Conf. on Intelligent
Robots and Systems (IROS)},
  year = 2013,
  month = nov,
  doi = {10.1109/IROS.2013.6696728},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beinhofer13iros.pdf},
  address = {Tokyo, Japan}
}
@inproceedings{hess13icra,
  author = {J{\"u}rgen Hess and Maximilian Beinhofer and Daniel Kuhner and Philipp Ruchti and Wolfram Burgard},
  title = {Poisson-Driven Dirt Maps for Efficient Robot
Cleaning},
  booktitle = {Proc.~of the IEEE Int. Conf. on Robotics \&
Automation (ICRA)},
  pages = {2245-2250},
  year = 2013,
  month = may,
  doi = {10.1109/ICRA.2013.6630880},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hess13icra.pdf},
  address = {Karlsruhe, Germany},
  abstract = {Being able to estimate the dirt distribution in an
                   environment makes it possible to compute efficient
                   paths for robotic cleaners. In this paper, we
                   present a novel approach for modeling and
                   estimating the dynamics of the generation of dirt
                   in an environment. Our model uses cell-wise Poisson
                   processes on a regular grid to estimate the
                   distribution of dirt in the environment. It allows
                   for an effective estimation of the dynamics of the
                   generation of dirt and for making predictions about
                   the absolute dirt values. We propose two efficient
                   cleaning policies that are based on the estimated
                   dirt distributions and can easily be adapted to
                   different needs of potential users. Through
                   extensive experiments carried out with a modified
                   iRobot Roomba vacuum cleaning robot and in
                   simulation we demonstrate the effectiveness of our
                   approach.},
  issn = {2153-0858}
}
@inproceedings{beinhofer13icra,
  author = {Maximilian Beinhofer and Henrik Kretzschmar and Wolfram Burgard},
  title = {Deploying Artificial Landmarks to Foster Data
Association in Simultaneous Localization and
Mapping},
  booktitle = {Proc.~of the IEEE Int. Conf. on Robotics \&
Automation (ICRA)},
  year = 2013,
  month = may,
  doi = {10.1109/ICRA.2013.6631325},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beinhofer13icra.pdf},
  address = {Karlsruhe, Germany}
}
@article{beinhofer13ras,
  author = {Maximilian Beinhofer and J{\"o}rg M{\"u}ller and Wolfram Burgard},
  title = {Effective Landmark Placement for Accurate and
Reliable Mobile Robot Navigation},
  journal = {Robotics and Autonomous Systems (RAS)},
  volume = {61},
  number = {10},
  pages = {1060 - 1069},
  year = 2013,
  doi = {10.1016/j.robot.2012.08.009},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beinhofer13ras.pdf},
  issn = {0921-8890}
}
@inproceedings{kuderer13iros,
  author = {Markus Kuderer and Henrik Kretzschmar and Wolfram Burgard},
  title = {Teaching Mobile Robots to Cooperatively
Navigate in Populated Environments},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2013,
  doi = {10.1109/IROS.2013.6696802},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuderer13iros.pdf},
  address = {Tokyo, Japan}
}
@inproceedings{kretzschmar13rldm,
  author = {Henrik Kretzschmar and Markus Kuderer and Wolfram Burgard},
  title = {Predicting Human Navigation Behavior via
Inverse Reinforcement Learning},
  booktitle = {The 1st Multidisciplinary Conference on
Reinforcement Learning and Decision Making (RLDM)},
  year = 2013,
  address = {Princeton, NJ, USA}
}
@inproceedings{kretzschmar13rss-ws,
  author = {Henrik Kretzschmar and Markus Kuderer and Wolfram Burgard},
  title = {Learning Navigation Policies from Human
Demonstrations},
  booktitle = {Proc.~of the Workshop on Inverse Optimal
Control \& Robotic Learning from Demonstration at
Robotics: Science and Systems (RSS)},
  year = 2013,
  address = {Berlin, Germany}
}
@inproceedings{kretzschmar13alw,
  author = {Henrik Kretzschmar and Markus Kuderer and Wolfram Burgard},
  title = {Inferring Navigation Policies for Mobile Robots
from Demonstrations},
  booktitle = {Proc.~of the Autonomous Learning Workshop at
the IEEE International Conference on Robotics and
Automation (ICRA)},
  year = 2013,
  address = {Karlsruhe, Germany}
}
@inproceedings{abdo13icra,
  author = {Nichola Abdo and Henrik Kretzschmar and Luciano Spinello and Cyrill Stachniss},
  title = {Learning Manipulation Actions from a Few
Demonstrations},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2013,
  doi = {10.1109/ICRA.2013.6630734},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/abdo13icra.pdf},
  address = {Karlsruhe, Germany}
}
@inproceedings{kuemmerle13icra,
  author = {K{\"u}mmerle, R and Ruhnke, M. and Steder, B. and  Stachniss, C. and Burgard, W.},
  title = {A Navigation System for Robots Operating in
Crowded Urban Environments},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle13icra.pdf},
  address = {Karlsruhe, Germany},
  abstract = {Over the past years, there has been a tremendous
                   progress in the area of robot navigation. Most of
                   the systems developed thus far, however, are
                   restricted to indoor scenarios, non-urban outdoor
                   environments, or road usage with cars. Urban areas
                   introduce numerous challenges to autonomous mobile
                   robots as they are highly complex and in addition
                   to that dynamic. In this paper, we present a
                   navigation system for pedestrian-like autonomous
                   navigation with mobile robots in city environments.
                   We describe different components including a SLAM
                   system for dealing with huge maps of city centers,
                   a planning approach for inferring feasible paths
                   taking also into account the traversability and
                   type of terrain, and a method for accurate
                   localization in dynamic environments. The
                   navigation system has been implemented and tested
                   in several large-scale field tests in which the
                   robot Obelix managed to autonomously navigate from
                   our university campus over a 3.3 km long route to
                   the city center of Freiburg.}
}
@phdthesis{kuemmerle13phd,
  author = {Rainer K{\"u}mmerle},
  title = {State Estimation and Optimization for Mobile
Robot Navigation},
  school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
  year = 2013,
  month = apr,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle-dissertation.pdf},
  downloads = {http://www.freidok.uni-freiburg.de/volltexte/8967/_FreiDok},
  downloads = {http://www.freidok.uni-freiburg.de/volltexte/8967/_FreiDok},
  abstract = {Robust autonomous navigation is a key feature of a
                   mobile robot realizing services such as
                   transportation, cleaning, search and rescue, and
                   surveillance. In addition to that, navigation is a
                   building block for a robot assisting humans in
                   potentially dangerous situations, such as search-
                   and-rescue scenarios. Hence, navigation is one of
                   the major research topics in the robotics
                   community. To realize the above mentioned
                   applications, we need to fulfill certain
                   requirements, so that a robot is regarded as
                   useful. For example, a robot which performs pick-
                   and-place tasks or offers guidance in city centers
                   needs to be aware of its own position in the
                   environment and it needs to have an accurate model
                   of the environment for planning an appropriate
                   path. A robot which should guide a human to a
                   certain place or has to deliver goods is only
                   regarded as helping hand, if the location is
                   reliably reached within the expected time frame.
                   Particularly, estimating the state which describes
                   the current situation of the navigation system is
                   complex. In this thesis, we focus on efficient and
                   accurate state estimation techniques which apply
                   probabilistic algorithms. An example for such a
                   state estimation task is the Simultaneous
                   Localization and Mapping (SLAM) problem, in which a
                   robot has to address both aspects. First, it needs
                   to estimate what the environment looks like. This
                   is the mapping part which deals with integrating
                   the information obtained by the sensors of the
                   robot into an appropriate representation. Second,
                   the localization component has to estimate the
                   position of the robot with respect to the model of
                   the environment. In the first part of this thesis,
                   we present efficient approaches to estimate the
                   state of the robot while performing SLAM. Our
                   approach allows a robot to accurately estimate the
                   model of the environment in an online setting and
                   also in situations when provided with a poor
                   initial guess. Additionally, we provide an
                   empirical evaluation which demonstrates the
                   advantages of our approach compared to other state-
                   of-the-art methods. Subsequently, we extend our
                   state estimation approach to also include the
                   unknown calibration parameters, which might change
                   during the lifetime of the robot, to incorporate
                   prior information about the structure of the
                   environment, and to improve the fine-grained
                   details of the estimated models. In the second part
                   of this thesis, we demonstrate two challenging
                   applications which we realized by building upon and
                   extending the algorithms presented in the first
                   part. In detail, we discuss an approach which
                   allows a car to autonomously park in a complex
                   multi-level parking garage. As second application
                   we present a robotic pedestrian assistant which is
                   able to navigate in densely populated pedestrian
                   zones. All techniques presented in this thesis have
                   been implemented and tested using both real-world
                   data collected with mobile robots and simulated
                   data. To support our claims, we performed an
                   extensive collection of experiments, in which we
                   compared the performance of our approaches with the
                   state-of-the- art. We believe that the proposed
                   approaches will allow us in the future to build
                   systems that can assist humans in their homes and
                   at their workplaces.}
}
@article{hoeflinger13tim,
  author = {H\"{o}flinger, F. and M\"{u}ller, J. and Zhang, R. and Burgard, W. and Reindl, L.M.},
  title = {A Wireless Micro Inertial Measurement Unit
({IMU})},
  journal = {IEEE Transactions on Instrumentation \&
Measurement},
  year = 2013,
  doi = {10.1109/TIM.2013.2255977},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hoeflinger13tim.pdf}
}
@inproceedings{riefert13vts,
  author = {Riefert, A. and M\"{u}ller, J. and Sauer, M. and Burgard, W. and Becker, B.},
  title = {Identification of Critical Variables using an
{FPGA}-based Fault Injection Framework},
  booktitle = {Proceedings of the IEEE VLSI Test Symposium
(VTS)},
  year = 2013,
  month = apr,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/riefert13vts.pdf},
  address = {Berkeley, CA, USA}
}
@article{mueller13ar,
  author = {M\"{u}ller, J. and Burgard, W.},
  title = {Efficient Probabilistic Localization for
Autonomous Indoor Airships using Sonar, Air Flow, and {IMU} Sensors},
  journal = {Advanced Robotics},
  volume = {27},
  number = {9},
  pages = {711-724},
  year = 2013,
  doi = {10.1080/01691864.2013.779005},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller13ar.pdf}
}
@inproceedings{riefert13tuz,
  author = {Riefert, A. and M\"{u}ller, J. and Sauer, M. and Burgard, W. and Becker, B.},
  title = {Identification of Critical Variables using an
{FPGA}-based Fault Injection Framework},
  booktitle = {Proceedings of the Workshop Testmethoden und
Zuverlässigkeit von Schaltungen und Systemen (TUZ)},
  year = 2013,
  month = feb,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/riefert13tuz.pdf},
  address = {Dresden, Germany}
}
@inproceedings{meyer13icraws,
  author = {Meyer, J. and Kuderer, M. and M\"{u}ller, J. and Burgard, W.},
  title = {Online Marker Labeling for Automatic Skeleton
Tracking in Optical Motion Capture},
  booktitle = {Proceedings of the ICRA Workshop on
Computational Techniques in Natural Motion Analysis
and Reconstruction},
  year = 2013,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyer13icraws.pdf},
  address = {Karlsruhe, Germany}
}
@techreport{sittel13regression,
  author = {Sittel, F. and M\"{u}ller, J. and Burgard, W.},
  title = {Computing Velocities and Accelerations from a
Pose Time Sequence in Three-dimensional Space},
  number = {272},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sittel13tr.pdf},
  institution = {University of Freiburg, Department of Computer
                   Science}
}
@phdthesis{mueller13phd,
  author = {J\"{o}rg M\"{u}ller},
  title = {Autonomous Navigation for Miniature Indoor
Airships},
  school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
  year = 2013,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller13phd.pdf}
}
@inproceedings{roewekaemper13iros,
  author = {J. Roewekaemper and G.D. Tipaldi and W. Burgard},
  title = {Learning to Guide Random Tree Planners in High
Dimensional Spaces},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/roewekaemper13iros.pdf},
  address = {Tokyo Big Sight, Japan}
}
@inproceedings{ruhnke13aaai,
  author = {Ruhnke, M. and Bo, L. and Fox, D. and Burgard, W.},
  title = {Compact {RGBD} Surface Models Based on Sparse
Coding},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke13aaai.pdf}
}
@article{lau13ras,
  author = {B. Lau and C. Sprunk and W. Burgard},
  title = {Efficient grid-based spatial representations
for robot navigation in dynamic environments},
  journal = {Robotics and Autonomous Systems},
  volume = {61},
  number = {10},
  pages = {1116--1130},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lau13ras.pdf}
}
@inproceedings{sprunk13iros,
  author = {C. Sprunk and G.D. Tipaldi and A. Cherubini and W. Burgard},
  title = {Lidar-based Teach-and-Repeat of Mobile Robot
Trajectories},
  booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent
Robots and Systems (IROS)},
  year = 2013,
  month = nov,
  doi = {10.1109/IROS.2013.6696803},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sprunk13iros.pdf},
  address = {Tokyo, Japan}
}
@inproceedings{dakulovic13iros,
  author = {M. Dakulovic and C. Sprunk and L. Spinello and I. Petrovic and W. Burgard},
  title = {Efficient Navigation for  Anyshape Holonomic
Mobile Robots in Dynamic Environments},
  booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent
Robots and Systems (IROS)},
  year = 2013,
  month = nov,
  doi = {10.1109/IROS.2013.6696729},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/dakulovic13iros.pdf},
  address = {Tokyo, Japan}
}
@inproceedings{bogoslavskyi13ecmr,
  author = {I. Bogoslavskyi and O. Vysotska and J. Serafin and G. Grisetti and C. Stachniss},
  title = {Efficient Traversability Analysis for Mobile
Robots using the Kinect Sensor},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bogoslavskyi13ecmr.pdf},
  address = {Barcelona, Spain}
}
@article{burgard13forschung,
  author = {W. Burgard and  C. Stachniss},
  title = {Gestatten, Obelix!},
  journal = {Forschung -- Das Magazin der Deutschen
Forschungsgemeinschaft},
  volume = {1},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/forschung_2013_01-pg4-9.pdf},
  note = {In German, invited}
}
@article{hornung13auro,
  author = {A. Hornung and K.M. Wurm and M. Bennewitz  and  C. Stachniss and W. Burgard},
  title = {{OctoMap}: An Efficient Probabilistic 3D
Mapping Framework Based on Octrees},
  journal = {Autonomous Robots},
  volume = {34},
  pages = {189-206},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hornung13auro.pdf},
  issue = {3}
}
@article{maier13ijhr,
  author = {D. Maier and C. Stachniss and M. Bennewitz},
  title = {Vision-Based Humanoid Navigation Using Self-
Supervised Obstacle Detection},
  journal = {The Int.~Journal of Humanoid Robotics (IJHR)},
  volume = {10},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/maier13ijhr.pdf},
  issue = {2}
}
@article{wurm13auro,
  author = {K.M. Wurm and C. Dornhege and B. Nebel and W. Burgard and  C. Stachniss},
  title = {Coordinating Heterogeneous Teams of Robots
using Temporal Symbolic Planning},
  journal = {Autonomous Robots},
  volume = {34},
  year = 2013,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm13auro.pdf},
  issue = {4}
}
@phdthesis{steder13phd,
  author = {Bastian Steder},
  title = {Feature-Based 3D Perception for Mobile Robots},
  school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
  year = 2013,
  month = apr,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder13phd.pdf},
  abstract = {Perception is one of the key topics in robotics
                   research. It is about the processing of external
                   sensor data and its interpretation. Strong
                   perceptual abilities are a basic requirement for a
                   robot working in an environment that was not
                   specifically designed for the robot. Such a
                   surrounding might be completely unknown or may
                   change over time, so that a model cannot be
                   provided to the robot a priori. Most people would
                   only judge a robot to be truly intelligent if it
                   perceives its environment, understands what is
                   happening around it and acts accordingly. This is
                   especially important in mobile robotics. A robot
                   that moves through an environment and interacts
                   with it has to know what is going on around it,
                   where it is, where it can go, and where objects
                   necessary for its task are located. The topic of
                   this thesis is the interpretation of low-level
                   sensor information and its application in high-
                   level tasks, specifically in the area of mobile
                   robotics. We mainly focus on 3D perception, meaning
                   the analysis and interpretation of 3D range scans.
                   This kind of data provides accurate spatial
                   information and is typically not dependent on the
                   light conditions. Spatial information is especially
                   important for navigation tasks, which, by nature,
                   are elementary for mobile platforms. To solve
                   different problems, we extract features from the
                   sensor data, which can then be used efficiently to
                   solve the task at hand. The term “feature” is
                   very broad in this context and means that some
                   useful information is derived from raw data, which
                   is easier to interpret than the original input. At
                   first, we discuss the benefits of point feature
                   extraction from 3D range scans, meaning the
                   detection of interesting areas and an efficient
                   description of the local data. Such point features
                   are typically employed for similarity measures
                   between chunks of data. We present an approach for
                   point feature extraction and then build on it to
                   create several systems that tackle highly relevant
                   topics of modern robotics. These include the
                   detection of known objects in a 3D scan, the
                   unsupervised creation of object models from a
                   collection of scans, the representation of an
                   environment with a small number of surface
                   primitives, and the ability to find the current
                   position of a robot based on a single 3D scan and a
                   database of already known places. All these
                   problems require an algorithm that detects similar
                   structures in homogeneous sensor data, i.e., to
                   find corresponding areas between 3D range scans. In
                   addition to this, we discuss a system where finding
                   correspondences between heterogeneous data types is
                   relevant. Specifically, we search for corresponding
                   areas in 3D range data and visual images, to
                   determine the position of a robot in an aerial
                   image. Finally, we present a complete robotic
                   system, designed to navigate as a pedestrian in an
                   urban environment. Such a system is built up from a
                   multitude of different modules, whereas high
                   robustness requirements apply to each of them to
                   ensure the reliability of the entire system. Our
                   core contribution to this system is a module that
                   analyzes the low-level sensor data and provides
                   high-level information to the other modules,
                   specifically, it performs a traversability analysis
                   and obstacle detection in 2D and 3D laser data. We
                   present several innovative algorithms and
                   techniques that advance the state of the art. We
                   use them to build systems that enable us to address
                   complex 3D perception problems, outperforming
                   existing approaches. We evaluate our methods in
                   challenging settings, focusing on realistic
                   applications and using real world data.}
}
@inproceedings{ahmad13icra,
  author = {Aamir Ahmad and Gian Diego Tipaldi and Pedro Lima and Wolfram Burgard},
  title = {Cooperative Robot Localization and Target
Tracking based on Least Square Minimization},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation ({ICRA})},
  year = 2013,
  doi = {10.1109/ICRA.2013.6631396},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ahmad13icra.pdf}
}
@inproceedings{tipaldi13icra,
  author = {Tipaldi, Gian Diego and Spinello, Luciano and Burgard, Wolfram},
  title = {Geometrical FLIRT Phrases for Large Scale Place
Recognition in 2D Range Data},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation ({ICRA})},
  year = 2013,
  doi = {10.1109/ICRA.2013.6630947},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/tipaldi13icra.pdf}
}
@article{tipaldi13ijrr,
  author = {Tipaldi, G. D. and Meyer-Delius, D. and Burgard, W.},
  title = {Lifelong localization in changing
environments},
  journal = {International Journal of Robotics Research},
  volume = {32},
  number = {14},
  year = 2013,
  month = dec,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/tipaldi13ijrr.pdf}
}
@inproceedings{meyerdelius12aaai,
  author = {Meyer-Delius, D. and Beinhofer, M. and Burgard, W.},
  title = {Occupancy Grid Models for Robot Mapping in
Changing Environments},
  booktitle = {Proc.~of the AAAI~Conf.~on Artificial
Intelligence (AAAI)},
  year = 2012,
  month = jul,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyerdelius12aaai.pdf},
  address = {Toronto, Canada}
}
@incollection{grundmann12book,
  author = {Grundmann, Thilo and Fiegert, Michael and Burgard, Wolfram},
  title = {Rule Set Based Joint State Update},
  booktitle = {Towards Service Robots for Everyday
Environments},
  pages = {301--326},
  year = 2012,
  publisher = {Springer}
}
@article{grzonka12tro_mvn,
  author = {Grzonka, S. and Karwath, A. and Dijoux, F. and Burgard, W.},
  title = {Activity-based Indoor Mapping and Estimation of
Human Trajectories},
  journal = {IEEE Transactions on Robotics (T-RO)},
  volume = {8},
  number = {1},
  pages = {234--245},
  year = 2012,
  month = mar,
  doi = {10.1109/TRO.2011.2165372},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka12tro_mvn.pdf}
}
@article{grzonka12tro_quad,
  author = {Grzonka, S. and Grisetti, G. and Burgard, W.},
  title = {A Fully Autonomous Indoor Quadrotor},
  journal = {IEEE Transactions on Robotics (T-RO)},
  volume = {8},
  number = {1},
  pages = {90--100},
  year = 2012,
  month = mar,
  doi = {10.1109/TRO.2011.2162999},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka12tro_quad.pdf}
}
@inproceedings{hess12iros,
  author = {J. Hess and D. Tipaldi and W. Burgard},
  title = {Null Space Optimization for Effective Coverage
of 3D Surfaces using Redundant Manipulators},
  booktitle = {Proc. of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  pages = {1923 -1928},
  year = 2012,
  doi = {10.1109/IROS.2012.6385960},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hess12iros.pdf},
  address = {Villamoura, Portugal},
  abstract = {In this paper we consider the problem of null
                   space minimization in coverage path planning of 3D
                   surfaces for redundant manipulators. Existing
                   coverage solutions only focus on Euclidean cost
                   functions and often return suboptimal paths with
                   respect to the joint space. In the approach
                   described here, we explicitly consider the null
                   space by treating different inverse kinematics
                   solutions as individual nodes in a graph and model
                   the problem as a generalized traveling salesman
                   problem (GTSP). The GTSP is a generalization of the
                   TSP where the nodes of the graph are subdivided
                   into clusters and at least one node in each cluster
                   needs to be visited. We evaluate our approach using
                   a PR2 robot and complex objects. Our results
                   demonstrate that our method outperforms Euclidean
                   coverage algorithms in terms of manipulation effort
                   and completion time.},
  issn = {2153-0858}
}
@inproceedings{joho12rss,
  author = {Dominik Joho and Gian Diego Tipaldi and Nikolas Engelhard and Cyrill Stachniss and Wolfram Burgard},
  title = {Nonparametric {B}ayesian Models for
Unsupervised Scene Analysis and Reconstruction},
  booktitle = {Proc. of Robotics: Science and Systems
{(RSS)}},
  year = 2012,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho12rss.pdf},
  address = {Sydney, Australia}
}
@inproceedings{joho12rssws,
  author = {Dominik Joho and Gian Diego Tipaldi and Nikolas Engelhard and Cyrill Stachniss and Wolfram Burgard},
  title = {Unsupervised Scene Analysis and Reconstruction
Using Nonparametric {B}ayesian Models},
  booktitle = {Proc. of the Workshop on Robots in Clutter at
Robotics: Science and Systems {(RSS)}},
  year = 2012,
  address = {Sydney, Australia}
}
@article{kretzschmar12ijrr,
  author = {Henrik Kretzschmar and Cyrill Stachniss},
  title = {Information-Theoretic Compression of Pose
Graphs for Laser-Based SLAM},
  journal = {The International Journal of Robotics Research
(IJRR)},
  volume = {31},
  pages = {1219--1230},
  year = 2012,
  doi = {10.1177/0278364912455072},
  url = {http://ijr.sagepub.com/content/31/11/1219},
  issue = {11}
}
@inproceedings{kuderer12rss,
  author = {Markus Kuderer and Henrik Kretzschmar and Christoph Sprunk and Wolfram Burgard},
  title = {Feature-Based Prediction of Trajectories for
Socially Compliant Navigation},
  booktitle = {Proc.~of Robotics: Science and Systems (RSS)},
  year = 2012,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuderer12rss.pdf},
  address = {Sydney, Australia}
}
@inproceedings{abdo12tampra,
  author = {Nichola Abdo and Henrik Kretzschmar and Cyrill Stachniss},
  title = {From Low-Level Trajectory Demonstrations to
Symbolic Actions for Planning},
  booktitle = {Proc.~of the ICAPS Workshop on Combining Task
and Motion Planning for Real-World Applications
(TAMPRA)},
  year = 2012,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/abdo12tampra.pdf},
  address = {Atibaia, S\~{a}o Paulo, Brazil}
}
@article{wurm13ras,
  author = {Wurm, K. M. and Kretzschmar, H. and K{\"u}mmerle, R. and Stachniss, C. and Burgard, W.},
  title = {Identifying Vegetation from Laser Data in
Structured Outdoor Environments},
  journal = {Robotics and Autonomous Systems},
  volume = {},
  number = {},
  pages = {-},
  year = 2012,
  doi = {10.1016/j.robot.2012.10.003},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm13ras.pdf},
  note = {In Press},
  issn = {0921-8890}
}
@article{kuemmerle12ar,
  author = {K{\"u}mmerle, R. and Grisetti, G. and Burgard, W.},
  title = {Simultaneous Parameter Calibration, Localization, and Mapping},
  journal = {Advanced Robotics},
  volume = {26},
  number = {17},
  pages = {2021--2041},
  year = 2012,
  doi = {10.1080/01691864.2012.728694},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle12ar.pdf},
  abstract = {The calibration parameters of a mobile robot play
                   a substantial role in navigation tasks. Often these
                   parameters are subject to variations that depend
                   either on changes in the environment or on the load
                   of the robot.  In this paper, we propose an
                   approach to simultaneously estimate a map of the
                   environment, the position of the on-board sensors
                   of the robot, and its kinematic parameters. Our
                   method requires no prior knowledge about the
                   environment and relies only on a rough initial
                   guess of the parameters of the platform. The
                   proposed approach estimates the parameters on-line
                   and it is able to adapt to non-stationary changes
                   of the configuration. We tested our approach in
                   simulated environments and on a wide range of real
                   world data using different types of robotic
                   platforms.}
}
@inproceedings{grisetti12iros,
  author = {Grisetti, G. and K{\"u}mmerle, R. and Ni, K.},
  title = {Robust Optimization of Factor Graphs by using
Condensed Measurements},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2012,
  month = oct,
  doi = {10.1109/IROS.2012.6385779},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti12iros.pdf},
  address = {Vilamoura, Portugal},
  abstract = {Popular problems in robotics and computer vision
                   like simultaneous localization and mapping (SLAM)
                   or structure from motion (SfM) require to solve a
                   least-squares problem that can be effectively
                   represented by factor graphs.  The chance to find
                   the global minimum of such problems depends on both
                   the initial guess and the non- linearity of the
                   sensor models. In this paper we propose an approach
                   to determine an approximation of the original
                   problem that has a larger convergence basin. To
                   this end, we employ a divide-and-conquer approach
                   that exploits the structure of the factor graph.
                   Our approach has been validated on real- world and
                   simulated experiments and is able to succeed in
                   finding the global minimum in situations where
                   other state-of-the-art methods fail.}
}
@inproceedings{sturm12iros,
  author = {J. Sturm and N. Engelhard and F. Endres and W. Burgard and D. Cremers},
  title = {A Benchmark for the Evaluation of {RGB-D SLAM} Systems},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2012,
  month = oct,
  doi = {10.1109/IROS.2012.6385773},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm12iros.pdf},
  address = {Vilamoura, Portugal}
}
@inproceedings{endres12robotik,
  author = {Felix Endres and Jürgen Hess and Wolfram Burgard},
  title = {Graph-Based Action Models for Human Motion Classification},
  booktitle = {ROBOTIK},
  year = 2012,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres12robotik.pdf}
}
@article{endres12at,
  author = {F. Endres and J. Hess and N. Engelhard and J. Sturm and W. Burgard},
  title = {6{D} Visual {SLAM} for {RGB-D} Sensors},
  journal = {at - Automatisierungstechnik},
  volume = {60},
  pages = {270--278},
  year = 2012,
  month = may,
  doi = {10.1524/auto.2012.0993},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres12at.pdf}
}
@inproceedings{endres12icra,
  author = {F. Endres and J. Hess and N. Engelhard and J. Sturm and D. Cremers and W. Burgard},
  title = {An Evaluation of the {RGB-D SLAM} System},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  year = 2012,
  month = may,
  doi = {10.1109/ICRA.2012.6225199},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres12icra.pdf},
  address = {St. Paul, Minnesota}
}
@inproceedings{ruhnke12icra,
  author = {Ruhnke, M. and K{\"u}mmerle, R. and Grisetti, G. and Burgard, W.},
  title = {Highly Accurate 3D Surface Models by Sparse
Surface Adjustment},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  year = 2012,
  month = may,
  doi = {10.1109/ICRA.2012.6225077},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke12icra.pdf},
  address = {St. Paul, MN, USA},
  abstract = {In this paper, we propose an approach to obtain
                   highly accurate 3D models from range data. The key
                   idea of our method is to jointly optimize the poses
                   of the sensor and the positions of the surface
                   points measured with a range scanning device. Our
                   approach applies a physical model of the underlying
                   range sensor. To solve the optimization task it
                   employs a state-of-the-art graph-based optimizer
                   and iteratively refines the structure of the error
                   function by recomputing the data associations after
                   each optimization.  We present our approach and
                   evaluate it on data recorded in different real
                   world environments with a RGBD camera and a laser
                   range scanner.  The experimental results
                   demonstrate that our method is able to
                   substantially improve the accuracy of SLAM results
                   and that it compares favorable over the moving
                   least squares method.}
}
@inproceedings{sprunk12icra,
  author = {C. Sprunk and B. Lau and W. Burgard},
  title = {Improved Non-linear Spline Fitting for Teaching
Trajectories to Mobile Robots},
  booktitle = {Proc. of the IEEE International Conference on
Robotics and Automation (ICRA)},
  pages = {2068--2073},
  year = 2012,
  month = may,
  doi = {10.1109/ICRA.2012.6224920},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sprunk12icra.pdf},
  address = {St. Paul, MN, USA}
}
@incollection{arras12star,
  author = {Kai O. Arras and Boris Lau and Slawomir Grzonka and Matthias Luber and Oscar Martinez Mozos and Daniel Meyer-Delius and Wolfram Burgard},
  title = {Range-Based People Detection and Tracking for
Socially Enabled Service Robots},
  booktitle = {Towards Service Robots for Everyday in
Environments},
  volume = {76},
  pages = {235--280},
  year = 2012,
  publisher = {Springer},
  editor = {Erwin Prassler and Rainer Bischoff and Wolfram
                   Burgard and Robert Haschke and Martin H\"{a}gele
                   and Gisbert Lawitzky and Bernhard Nebel and Paul
                   Pl\"{o}ger and Ulrich Reiser and Marius
                   Z\"{o}llner},
  series = {Springer Tracts in Advanced Robotics (STAR)}
}
@inproceedings{mueller12icra,
  author = {M\"{u}ller, J. and Paul, O. and Burgard, W.},
  title = {Probabilistic Velocity Estimation for
Autonomous Miniature Airships using Thermal Air Flow
Sensors},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics \& Automation (ICRA)},
  pages = {39-44},
  year = 2012,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller12icra.pdf},
  address = {Saint Paul, MN, USA}
}
@inproceedings{hoeflinger12i2mtc,
  author = {H\"{o}flinger, F. and M\"{u}ller, J. and T\"{o}rk, M. and Reindl, L.M. and Burgard, W.},
  title = {A Wireless Micro Inertial Measurement Unit
({IMU})},
  booktitle = {Proceedings of the IEEE International
Instrumentation and Measurement Technology
Conference (I2MTC)},
  pages = {2578-2583},
  year = 2012,
  month = may,
  doi = {10.1109/I2MTC.2012.6229271},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hoeflinger12i2mtc.pdf},
  address = {Graz, Austria}
}
@inproceedings{wendeberg12ipin,
  author = {Wendeberg, J. and M\"{u}ller, J. and Schindelhauer, C. and Burgard, W.},
  title = {Robust Tracking of a Mobile Beacon using Time
Differences of Arrival with Simultaneous Calibration
of Receiver Positions},
  booktitle = {Proceedings of the International Conference on
Indoor Positioning and Indoor Navigation (IPIN)},
  year = 2012,
  month = nov,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wendeberg12ipin.pdf},
  address = {Sydney, Australia}
}
@inproceedings{demeester12icscs,
  author = {E. Demeester and E. Vander Poorten and A. Hüntemann and J. De Schutter and M. Hofmann and M. Rooker and G. Kronreif and B. Lau and M. Kuderer and W. Burgard and A . Gelin, K. Vanopdenbosch and P. Van der Beeten and M. Vereecken and S. Ilsbroukx and A. Fossati and G. Roig and X. Boix and L. Van Gool and H. Fraeyman and L. Broucke and H. Goessaert and J. Josten},
  title = {Robotic ADaptation to Humans Adapting to
Robots: Overview of the FP7 project RADHAR},
  booktitle = {International Conference on Systems and
Computer Science (ICSCS)},
  year = 2012,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/demeester12icscs.pdf}
}
@inproceedings{roewekaemper12iros,
  author = {J. Roewekaemper and C. Sprunk and G.D. Tipaldi and  C. Stachniss and P. Pfaff and W. Burgard},
  title = {On the Position Accuracy of Mobile Robot Localization based on Particle Filters combined with Scan Matching},
  booktitle = {Proc.~of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages = {3158--3164},
  year = 2012,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/roewekaemper12iros.pdf},
  address = {Villamoura, Portugal}
}
@article{stachniss12fnt,
  author = {C. Stachniss and W. Burgard},
  title = {Particle Filters for Robot Navigation},
  journal = {Foundations and Trends in Robotics},
  volume = {3},
  number = {4},
  pages = {211-282},
  year = 2012,
  doi = {10.1561/2300000013},
  note = {Published 2014}
}
@book{sc12proceedings,
  title = {Spatial Cognition VIII},
  year = 2012,
  month = aug,
  publisher = {Springer},
  editor = {C. Stachniss and K. Schill and D. Uttal}
}
@inproceedings{grisetti12rich,
  author = {G. Grisetti and  L. Iocchi and B. Leibe and V.A. Ziparo and C. Stachniss},
  title = {Digitization of Inaccessible Archeological
Sites with Autonomous Mobile Robots},
  booktitle = {Conf.~on Robotics Innovation for Cultural
Heritage},
  year = 2012,
  notes = {Extended abstract}
}
@inproceedings{spinello12rssws,
  author = {L. Spinello and C. Stachniss and W. Burgard},
  title = {Scene in the Loop: Towards Adaptation-by-
Tracking in RGB-D Data},
  booktitle = {Proc.~of the RSS Workshop RGB-D: Advanced
Reasoning with Depth Cameras},
  year = 2012,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/spinello12rssws.pdf}
}
@article{ruhnke12desire,
  author = {Ruhnke, M. and Steder, B. and Grisetti, G. and Burgard, W.},
  title = {{3D} Environment Modeling Based on Surface
Primitives},
  journal = {Towards Service Robots for Everyday
Environments},
  pages = {281--300},
  year = 2012,
  publisher = {Springer Berlin/Heidelberg},
  abstract = {In this chapter we describe an algorithm for
                   constructing a compact representation of 3D laser
                   range data. Our approach extracts a dictionary of
                   local scans from the scene. The words of this
                   dictionary are used to replace recurrent local 3D
                   structures, which leads to a substantial
                   compression of the entire point cloud.  We optimize
                   our model in terms of complexity and accuracy by
                   minimizing the Bayesian information criterion
                   (BIC). Experimental evaluations on large real-world
                   datasets show that the described method allows
                   robots to accurately reconstruct en- vironments
                   with as few as 70 words. Furthermore the
                   experiments suggest that the proposed
                   representation gives a richer semantic description
                   than pure occupancy based representations.}
}
@inproceedings{tipaldi12rssws,
  author = {Tipaldi, G. D. and Meyer-Delius, D. and Beinhofer, M. and Burgard, W.},
  title = {Lifelong Localization and Dynamic Map
Estimation in Changing Environments},
  booktitle = {RSS Workshop on Robots in Clutter:
Manipulation, Perception and Navigation in Human
Environments},
  year = 2012
}
@phdthesis{wurm12phd,
  author = {Kai M.~Wurm},
  title = {Techniques for Multi-Robot Coordination and
Navigation},
  school = {Albert-Ludwigs-University of Freiburg, Department of Computer Science},
  year = 2012,
  month = oct,
  url = {http://www.freidok.uni-freiburg.de/volltexte/8774}
}
@inproceedings{cunningham12icra,
  author = {A. Cunningham and K.M. Wurm and W. Burgard and F. Dellaert},
  title = {Fully Distributed Scalable Smoothing and
Mapping with Robust Multi-robot Data Association},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Robotics \& Automation (ICRA)},
  year = 2012,
  doi = {10.1109/ICRA.2012.6225356},
  address = {Saint Paul, MN, USA}
}
@inproceedings{beinhofer11ecmr,
  author = {Beinhofer, M. and M{\"u}ller, J. and Burgard, W.},
  title = {Landmark Placement for Accurate Mobile Robot
Navigation},
  booktitle = {Proc.~of the European~Conf.~on Mobile Robots
(ECMR)},
  pages = {55-60},
  year = 2011,
  month = sep,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beinhofer11ecmr.pdf},
  address = {{\"O}rebro, Sweden}
}
@inproceedings{tipaldi11irosWS,
  author = {Tipaldi, G. and Meyer-Delius, D. and Beinhofer, M. and Burgard, W.},
  title = {Simultaneous Localization and Dynamic State
Estimation in Reconfigurable Environments},
  booktitle = {Proc.~of the IEEE/RSJ IROS Workshop on Metrics
and Methodologies for Autonomous Robot Teams in
Logistics (MMART-LoG)},
  year = 2011,
  month = oct,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/tipaldi11irosWS.pdf},
  address = {San Francisco, USA}
}
@techreport{meyerdelius11alufr,
  author = {Meyer-Delius, D. and Beinhofer, M. and Burgard, W.},
  title = {Grid-Based Models for Dynamic Environments},
  year = 2011,
  month = jul,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/report00265.pdf},
  institution = {Dept.~of Computer Science, University of
                   Freiburg}
}
@inproceedings{beinhofer11icra,
  author = {Beinhofer, M. and M{\"u}ller, J. and Burgard, W.},
  title = {Near-optimal Landmark Selection for Mobile
Robot Navigation},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  pages = {4744-4749},
  year = 2011,
  month = may,
  doi = {10.1109/ICRA.2011.5979871},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beinhofer11icra.pdf},
  address = {Shanghai, China}
}
@inproceedings{meyerdelius11icra,
  author = {Meyer-Delius, D. and Beinhofer, M. and Kleiner, A. and Burgard, W.},
  title = {Using Artificial Landmarks to Reduce the
Ambiguity in the Environment of a Mobile Robot},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  pages = {5173-5178},
  year = 2011,
  month = may,
  doi = {10.1109/ICRA.2011.5980111},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyerdelius11icra.pdf},
  address = {Shanghai, China}
}
@phdthesis{grzonkaPhd,
  author = {Grzonka, Slawomir},
  title = {Mapping, State Estimation, and Navigation for
Quadrotors and Human-Worn Sensor Systems},
  school = {Albert-Ludwigs-University of Freiburg},
  year = 2011,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonkaPhd.pdf}
}
@inproceedings{grzonka11rssws,
  author = {Grzonka, S. and Steder, B. and Burgard, W.},
  title = {3D Place Recognition and Object Detection using
a Small-sized Quadrotor},
  booktitle = {Workshop on 3D Exploration, Mapping, and
Surveillance with Aerial Robots at Robotics: Science
and Systems (RSS)},
  year = 2011,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka11rssws.pdf}
}
@article{bouabdallah10irs,
  author = {Bouabdallah, S. and Bermes, C. and Grzonka, S. and Gimkiewicz, C. and Brenzikofer, A. and Hahn, R. and Schafroth, D. and Grisetti, G. and Burgard, W. and Siegwart, R.},
  title = {Towards Palm-Size Autonomous Helicopters},
  journal = {Journal of Intelligent \& Robotic Systems},
  volume = {61},
  pages = {1--27},
  year = 2011,
  issue = {1-4}
}
@article{joho11ras,
  author = {Dominik Joho and Martin Senk and Wolfram Burgard},
  title = {Learning Search Heuristics for Finding Objects
in Structured Environments},
  journal = {Robotics and Autonomous Systems},
  volume = {59},
  number = {5},
  pages = {319--328},
  year = 2011,
  month = may,
  doi = {10.1016/j.robot.2011.02.012},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho11ras.pdf},
  issn = {0921-8890}
}
@inproceedings{stachniss11isrr,
  author = {Cyrill Stachniss and Henrik Kretzschmar},
  title = {Pose Graph Compression for Laser-Based {SLAM}},
  booktitle = {Proc.~of the International Symposium of
Robotics Research (ISRR)},
  year = 2011,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss11isrr.pdf},
  note = {Invited presentation.},
  address = {Flagstaff, AZ, USA}
}
@inproceedings{ziegler11iros,
  author = {Jakob Ziegler and Henrik Kretzschmar and Cyrill Stachniss and Giorgio Grisetti and Wolfram Burgard},
  title = {Accurate Human Motion Capture in Large Areas by
Combining {IMU}- and Laser-Based People Tracking},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  pages = {86--91},
  year = 2011,
  doi = {10.1109/IROS.2011.6094430},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ziegler11iros.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{kretzschmar11iros,
  author = {Henrik Kretzschmar and Cyrill Stachniss and Giorgio Grisetti},
  title = {Efficient Information-Theoretic Graph Pruning
for Graph-Based {SLAM} with Laser Range Finders},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  pages = {865--871},
  year = 2011,
  doi = {10.1109/IROS.2011.6094414},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kretzschmar11iros.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{kuemmerle11arso,
  author = {K{\"u}mmerle, R. and Grisetti, G. and Stachniss, C. and Burgard, W.},
  title = {Simultaneous Parameter Calibration, Localization, and Mapping for Robust Service
Robotics},
  booktitle = {Proc. of the IEEE Workshop on Advanced Robotics
and its Social Impacts (ARSO)},
  year = 2011,
  month = oct,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle11arso.pdf},
  address = {Half Moon Bay, CA, USA},
  abstract = {Modern service robots are designed to be deployed
                   by end-users and not to be monitored by experts
                   during operation. Most service robotics
                   applications require reliable navigation
                   capabilities of the robot.  The calibration
                   parameters of a mobile robot play a substantial
                   role in navigation tasks. Often these parameters
                   are subject to variations that depend either on
                   environmental changes or on the wear of the
                   devices. In this paper, we propose an approach to
                   simultaneously estimate a map of the environment,
                   the position of the on-board sensors of the robot,
                   and its kinematic parameters. Our method requires
                   no prior knowledge about the environment and relies
                   only on a rough initial guess of the platform
                   parameters. The proposed approach performs on-line
                   estimation of the parameters and it is able to
                   adapt to non-stationary changes of the
                   configuration.  Our approach has been implemented
                   and is used on the EUROPA robot, a service robot
                   operating in urban environments. In addition to
                   that, we tested our approach in simulated
                   environments and on a wide range of real world data
                   using different types of robotic platforms.}
}
@inproceedings{ruhnke11arso,
  author = {Ruhnke, M. and K{\"u}mmerle, R. and Grisetti, G. and Burgard, W.},
  title = {Range Sensor Based Model Construction by Sparse
Surface Adjustment},
  booktitle = {Proc. of the IEEE Workshop on Advanced Robotics
and its Social Impacts (ARSO)},
  year = 2011,
  month = oct,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke11arso.pdf},
  address = {Half Moon Bay, CA, USA},
  abstract = {In this paper, we propose an approach to construct
                   highly accurate 3D object models from range data.
                   The main advantage of sensor based model
                   acquisition compared to manual CAD model
                   construction is the short time needed per object.
                   The usual drawbacks of sensor based model
                   reconstruction are sensor noise and errors in the
                   sensor positions which typically lead to less
                   accurate  models. Our method drastically reduces
                   this problem by applying a physical model of the
                   underlying range sensor and utilizing a graph-based
                   optimization technique.  We present our approach
                   and evaluate it on data recorded in different real
                   world environments with an RGBD camera and a laser
                   range scanner.  The experimental results
                   demonstrate that our method provides more accurate
                   maps than standard SLAM  methods and that it
                   additionally compares favorable over the moving
                   least squares method.}
}
@inproceedings{kuemmerle11iros,
  author = {K{\"u}mmerle, R. and Grisetti, G. and Burgard, W.},
  title = {Simultaneous Calibration, Localization, and
Mapping},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2011,
  month = sep,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle11iros.pdf},
  address = {San Francisco, CA, USA},
  abstract = {The calibration parameters of a mobile robot play
                   a substantial role in navigation tasks. Often these
                   parameters are subject to variations that depend
                   either on environmental changes or on the wear of
                   the devices.  In this paper, we propose an approach
                   to simultaneously estimate a map of the
                   environment, the position of the on-board sensors
                   of the robot, and its kinematic parameters. Our
                   method requires no prior knowledge about the
                   environment and relies only on a rough initial
                   guess of the platform parameters. The proposed
                   approach performs on-line estimation of the
                   parameters and it is able to adapt to non-
                   stationary changes of the configuration. We tested
                   our approach in simulated environments and on a
                   wide range of real world data using different types
                   of robotic platforms.}
}
@inproceedings{kuemmerle11icra,
  author = {K{\"u}mmerle, R. and Grisetti, G. and Strasdat, H. and Konolige, K. and Burgard, W.},
  title = {g2o: A General Framework for Graph
Optimization},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  year = 2011,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle11icra.pdf},
  downloads = {http://openslam.org/g2o_Open_source_implementation_(stable);
https://github.com/RainerKuemmerle/g2o_Open_source_implementation_(devel)},
  downloads = {http://openslam.org/g2o_Open_source_implementation_(stable);
https://github.com/RainerKuemmerle/g2o_Open_source_implementation_(devel)},
  address = {Shanghai, China},
  abstract = {Many popular problems in robotics and computer
                   vision including various types of simultaneous
                   localization and mapping (SLAM) or bundle
                   adjustment (BA) can be phrased as least squares
                   optimization of an error function that can be
                   represented by a graph. This paper describes the
                   general structure of such problems and presents
                   g2o, an open-source C++ framework for optimizing
                   graph-based nonlinear error functions.  Our system
                   has been designed to be easily extensible to a wide
                   range of problems and a new problem typically can
                   be specified in a few lines of code.  The current
                   implementation provides solutions to several
                   variants of SLAM and BA. We provide evaluations on
                   a wide range of real-world and simulated datasets.
                   The results demonstrate that while being general
                   g2o offers a performance comparable to
                   implementations of state-of-the-art approaches for
                   the specific problems.}
}
@inproceedings{ruhnke11icra,
  author = {Ruhnke, M. and K{\"u}mmerle, R. and Grisetti, G. and Burgard, W.},
  title = {Highly Accurate Maximum Likelihood Laser
Mapping by Jointly Optimizing Laser Points and Robot
Poses},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics and
Automation (ICRA)},
  year = 2011,
  month = may,
  doi = {10.1109/ICRA.2011.5980220},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke11icra.pdf},
  address = {Shanghai, China},
  abstract = {In this paper we describe an algorithm for
                   learning highly accurate laser-based maps that
                   treats the overall mapping problem as a joint
                   optimization problem over robot poses and laser
                   points.  We assume that a laser range finder senses
                   points sampled from a regular surface and we
                   utilize an improved likelihood function that
                   accounts for two phenomena affecting the laser
                   measurements that are often neglected: the conic
                   shape of the laser beam and the incidence angle.
                   To solve the entire problem we apply an
                   optimization procedure that jointly adjusts the
                   position of all the robot poses and all points in
                   the scans.  As a result, we obtain highly accurate
                   maps. We evaluated our approach using simulated and
                   real-world data and we show that utilizing the
                   estimated maps greatly improves the localization
                   accuracy of robots.  The results furthermore
                   suggest that the accuracy of the resulting map can
                   exceed the resolution of the laser sensors used.}
}
@article{kuemmerle11auro,
  author = {R. K\"ummerle and B. Steder and C. Dornhege and A. Kleiner and G. Grisetti and W. Burgard},
  title = {Large Scale Graph-based {SLAM} using Aerial
Images as Prior Information},
  journal = {Journal of Autonomous Robots},
  volume = {30},
  number = {1},
  pages = {25--39},
  year = 2011,
  doi = {10.1007/s10514-010-9204-1},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle11auro.pdf},
  downloads = {http://dx.doi.org/10.1007/s10514-010-9204-1_Online_Version},
  downloads = {http://dx.doi.org/10.1007/s10514-010-9204-1_Online_Version},
  abstract = {The problem of learning a map with a mobile robot
                   has been intensively studied in the past and is
                   usually referred to as the simultaneous
                   localization and mapping (SLAM) problem. However,
                   most existing solutions to the SLAM problem learn
                   the maps from scratch and have no means for
                   incorporating prior information. In this paper, we
                   present a novel SLAM approach that achieves global
                   consistency by utilizing publicly accessible aerial
                   photographs as prior information. It inserts
                   correspondences found between stereo and three-
                   dimensional range data and the aerial images as
                   constraints into a graph-based formulation of the
                   SLAM problem. We evaluate our algorithm based on
                   large real-world datasets acquired even in mixed
                   in- and outdoor environments by comparing the
                   global accuracy with state-of-the-art SLAM
                   approaches and GPS. The experimental results
                   demonstrate that the maps acquired with our method
                   show increased global consistency.}
}
@inproceedings{lau11ecmr,
  author = {Boris Lau and Christoph Sprunk and Wolfram Burgard},
  title = {Incremental Updates of Configuration Space
Representations for Non-Circular Mobile Robots with
2D, 2.5D, or 3D Obstacle Models},
  booktitle = {European Conference on Mobile Robots (ECMR)},
  pages = {49--54},
  year = 2011,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lau11ecmr.pdf},
  address = {\"{O}rebro, Sweden}
}
@inproceedings{sauer11iolts,
  author = {Sauer, M. and Tomashevich, V. and M\"{u}ller, J. and Lewis, M. and Spilla, A. and Polian, I. and Becker, B. and Burgard, W.},
  title = {An {FPGA}-Based Framework for Run-time
Injection and Analysis of Soft Errors in
Microprocessors},
  booktitle = {Proceedings of the IEEE International On-Line
Testing Symposium (IOLTS)},
  pages = {182-185},
  year = 2011,
  month = jul,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sauer11iolts.pdf},
  address = {Athens, Greece}
}
@inproceedings{spilla11tuz,
  author = {Spilla, A. and Polian, I. and M\"{u}ller, J. and Lewis, M. and Tomashevich, V. and Becker, B. and Burgard, W.},
  title = {Run-time Soft Error Injection and Testing of a
Microprocessor using {FPGAs}.},
  booktitle = {Proceedings of the Workshop Testmethoden und
Zuverlässigkeit von Schaltungen und Systemen (TUZ)},
  year = 2011,
  month = feb,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/spilla11tuz.pdf},
  address = {Passau, Germany}
}
@inproceedings{mueller11iros,
  author = {M\"{u}ller, J. and Kohler, N. and Burgard, W.},
  title = {Autonomous Miniature Blimp Navigation with
Online Motion Planning and Re-planning},
  booktitle = {Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems
(IROS)},
  pages = {4941-4946},
  year = 2011,
  month = sep,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller11iros.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{steder11iros,
  author = {Steder, B. and Ruhnke, M. and Grzonka, S. and Burgard, W.},
  title = {Place Recognition in 3D Scans Using a
Combination of Bag of Words and Point Feature based
Relative Pose Estimation},
  booktitle = {Proc.~of the Int.~Conf.~on Intelligent Robots
and Systems (IROS)},
  year = 2011,
  doi = {10.1109/IROS.2011.6094638},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder11iros.pdf},
  abstract = {Place recognition, i.e., the ability to recognize
                   previously seen parts of the environment, is one of
                   the fundamental tasks in mobile robotics. The wide
                   range of applications of place recognition includes
                   localization (determine the initial pose), SLAM
                   (detect loop closures), and change detection in
                   dynamic environments. In the past, only relatively
                   little work has been carried out to attack this
                   problem using 3D range data and the majority of
                   approaches focuses on detecting similar structures
                   without estimating relative poses. In this paper,
                   we present an algorithm based on 3D range data that
                   is able to reliably detect previously seen parts of
                   the environment and at the same time calculates an
                   accurate transformation between the corresponding
                   scan-pairs. Our system uses the estimated
                   transformation to evaluate a candidate and in this
                   way to more robustly reject false positives for
                   place recognition. We present an extensive set of
                   experiments using publicly available datasets in
                   which we compare our system to other state-of-the-
                   art approaches.}
}
@inproceedings{sprunk11icra,
  author = {C. Sprunk and B. Lau and P. Pfaff and W. Burgard},
  title = {Online Generation of Kinodynamic Trajectories
for Non-Circular Omnidirectional Robots},
  booktitle = {Proc. of the IEEE International Conference on
Robotics and Automation (ICRA)},
  pages = {72--77},
  year = 2011,
  month = may,
  doi = {10.1109/ICRA.2011.5980146},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sprunk11icra.pdf},
  address = {Shanghai, China}
}
@article{sturm11jair,
  author = {J. Sturm and C. Stachniss and W. Burgard},
  title = {A Probabilistic Framework for Learning
Kinematic Models of Articulated Objects},
  journal = {Journal on Artificial Intelligence Research},
  volume = {41},
  pages = {477--526},
  year = 2011,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm11jair.pdf}
}
@inproceedings{bennewitz11humanoids,
  author = {M. Bennewitz and D. Maier and A. Hornung and C. Stachniss},
  title = {Integrated Perception and Navigation in Complex
Indoor Environments},
  booktitle = {Proc.~of the IEEE-RAS Int.~Conf.~on Humanoid
Robots (HUMANOIDS)},
  year = 2011,
  note = {Invited presentation at the workshop on Humanoid
                   service robot navigation in crowded and dynamic
                   environments}
}
@inproceedings{becker11irosws,
  author = {J. Becker and C. Bersch and D. Pangercic and B. Pitzer and T. R\"uhr and B. Sankaran and J. Sturm and C. Stachniss and M. Beetz and W. Burgard},
  title = {Mobile Manipulation of Kitchen Containers},
  booktitle = {Proc.~of the IROS'11 Workshop on Results, Challenges and Lessons Learned in Advancing Robots
with a Common Platform},
  year = 2011,
  doi = {10.1109/ICRA.2011.5980259},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/becker11irosws.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{wurm11iros,
  author = {K.M. Wurm  and D. Hennes  and D. Holz and R.B. Rusu and C. Stachniss and K. Konolige and W. Burgard},
  title = {Hierarchies of Octrees for Efficient 3D
Mapping},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2011,
  month = sep,
  doi = {10.1109/IROS.2011.6094571},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm11iros.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{frank11iros,
  author = {B. Frank and C. Stachniss and N. Abdo and W. Burgard},
  title = {Efficient Motion Planning for Manipulation
Robots in Environments with Deformable Objects},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2011,
  doi = {10.1109/IROS.2011.6094946},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank11iros.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{frank11pamr,
  author = {B. Frank and C. Stachniss and N. Abdo and W. Burgard},
  title = {Using Gaussian Process Regression for Efficient
Motion Planning in Environments with Deformable
Objects},
  booktitle = {Proc. of the AAAI-11 Workshop on Automated
Action Planning for Autonomous Mobile Robots
(PAMR)},
  year = 2011,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank11pamr.pdf},
  address = {San Francisco, CA, USA}
}
@inproceedings{maier11icra,
  author = {D. Maier and M. Bennewitz and C. Stachniss},
  title = {Self-supervised Obstacle Detection for Humanoid
Navigation Using Monocular Vision and Sparse Laser
Data},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2011,
  doi = {10.1109/ICRA.2011.5979661},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/maier11icra.pdf},
  address = {Shanghai, China}
}
@inbook{asadi11gasbook,
  author = {S. Asadi and M. Reggente and  C. Stachniss and  C. Plagemann and A.J. Lilienthal},
  title = {Intelligent Systems for Machine Olfaction:
Tools and Methodologies},
  pages = {153-179},
  year = 2011,
  chapter = {Statistical Gas Distribution Modelling using
                   Kernel Methods},
  publisher = {{IGI} {G}lobal},
  editor = {E.L. Hines and  M.S. Leeson}
}
@inproceedings{steder11icra,
  author = {B. Steder and R. B. Rusu and K. Konolige and W. Burgard},
  title = {Point Feature Extraction on {3D} Range Scans
Taking into Account Object Boundaries},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2011,
  doi = {10.1109/ICRA.2011.5980187},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder11icra.pdf},
  abstract = {In this paper we address the topic of feature
                   extraction in 3D point cloud data for object
                   recognition and pose identification. We present a
                   novel interest keypoint extraction method that
                   operates on range images generated from arbitrary
                   3D point clouds, which explicitly considers the
                   borders of the objects identified by transitions
                   from foreground to background. We furthermore
                   present a feature descriptor that takes the same
                   information into account.  We have implemented our
                   approach and present rigorous experiments in which
                   we analyze the individual components with respect
                   to their repeatability and matching capabilities
                   and evaluate the usefulness for point feature based
                   object detection methods.}
}
@inproceedings{grundmann10iros,
  author = {Grundmann, Thilo and Fiegert, Michael and Burgard, Wolfram},
  title = {Probabilistic rule set joint state update as
approximation to the full joint state estimation
applied to multi object scene analysis},
  booktitle = {Proc. of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  pages = {2047--2052},
  year = 2010,
  doi = {10.1109/IROS.2010.5650433}
}
@inproceedings{bouabdallah10uav,
  author = {Bouabdallah, S. and Bermes, C. and Grzonka, S. and Gimkiewicz, C. and Brenzikofer, A. and Hahn, R. and Schafroth, D. and Grisetti, G. and Burgard, W. and Siegwart, R.},
  title = {Towards Palm-Size Autonomous Helicopters},
  booktitle = {International Conference and Exhibition on
Unmanned Areal Vehicles (UAV)},
  year = 2010,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bouabdallah10uav.pdf}
}
@inproceedings{grzonka10icra,
  author = {Grzonka, S. and Dijoux, F. and Karwath, A. and Burgard, W.},
  title = {Mapping Indoor Environments Based on Human
Activity},
  booktitle = {Proc. IEEE International Conference on Robotics
and Automation (ICRA)},
  year = 2010,
  doi = {10.1109/ROBOT.2010.5509976},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka10icra.pdf},
  address = {Anchorage, Ak, USA}
}
@inproceedings{joho10icra,
  author = {Dominik Joho and Wolfram Burgard},
  title = {Searching for Objects: Combining Multiple Cues
To Object Locations Using a Maximum Entropy Model},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation {(ICRA)}},
  pages = {723--728},
  year = 2010,
  month = may,
  doi = {10.1109/ROBOT.2010.5509285},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho10icra.pdf},
  isbn = {978-1-4244-5038-1},
  address = {Anchorage, AK, USA},
  issn = {1050-4729}
}
@article{kretzschmar10ki,
  author = {Henrik Kretzschmar and Giorgio Grisetti and Cyrill Stachniss},
  title = {Lifelong Map Learning for Graph-based {SLAM} in
Static Environments},
  journal = {{KI} -- {K}\"unstliche {I}ntelligenz},
  volume = {24},
  pages = {199--206},
  year = 2010,
  doi = {10.1007/s13218-010-0034-2},
  issue = {3}
}
@article{grisetti10titsmag,
  author = {G. Grisetti and R. K{\"u}mmerle and C. Stachniss and W. Burgard},
  title = {A Tutorial on Graph-Based {SLAM}},
  journal = {Intelligent Transportation Systems Magazine, IEEE},
  volume = {2},
  number = {4},
  pages = {31--43},
  year = 2010,
  doi = {10.1109/MITS.2010.939925},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti10titsmag.pdf},
  downloads = {http://dx.doi.org/10.1109/MITS.2010.939925_Online_Version},
  downloads = {http://dx.doi.org/10.1109/MITS.2010.939925_Online_Version},
  abstract = {Being able to build a map of the environment and
                   to simultaneously localize within this map is an
                   essential skill for mobile robots navigating in
                   unknown environments in absence of external
                   referencing systems such as GPS. This so-called
                   simultaneous localization and mapping (SLAM)
                   problem has been one of the most popular research
                   topics in mobile robotics for the last two decades
                   and efficient approaches for solving this task have
                   been proposed. One intuitive way of formulating
                   SLAM is to use a graph whose nodes correspond to
                   the poses of the robot at different points in time
                   and whose edges represent constraints between the
                   poses. The latter are obtained from observations of
                   the environment or from movement actions carried
                   out by the robot. Once such a graph is constructed,
                   the map can be computed by finding the spatial
                   configuration of the nodes that is mostly
                   consistent with the measurements modeled by the
                   edges. In this paper, we provide an introductory
                   description to the graph- based SLAM problem.
                   Furthermore, we discuss a state- of-the-art
                   solution that is based on least-squares error
                   minimization and exploits the structure of the SLAM
                   problems during optimization. The goal of this
                   tutorial is to enable the reader to implement the
                   proposed methods from scratch.},
  issue = {4}
}
@inproceedings{konolige10iros,
  author = {K. Konolige and G. Grisetti and R. K{\"u}mmerle and W. Burgard and B. Limketkai and R. Vincent},
  title = {Efficient Sparse Pose Adjustment for 2D
Mapping},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2010,
  month = oct,
  doi = {10.1109/IROS.2010.5649043},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/konolige10iros.pdf},
  downloads = {http://www.ros.org/research/2010/spa/_2D_Data_sets;
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/spa-iros.mp4_Movie_(6.6_MB)},
  downloads = {http://www.ros.org/research/2010/spa/_2D_Data_sets;
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/spa-iros.mp4_Movie_(6.6_MB)},
  address = {Taipei, Taiwan},
  abstract = {Pose graphs have become a popular representation
                   for solving the simultaneous localization and
                   mapping (SLAM) problem. A pose graph is a set of
                   robot poses connected by nonlinear constraints
                   obtained from observations of features common to
                   nearby poses. Optimizing large pose graphs has been
                   a bottleneck for mobile robots, since the
                   computation time of direct nonlinear optimization
                   can grow cubically with the size of the graph. In
                   this paper, we propose an efficient method for
                   constructing and solving the linear subproblem,
                   which is the bottleneck of these direct methods. We
                   compare our method, called Sparse Pose Adjustment
                   (SPA), with competing indirect methods, and show
                   that it outperforms them in terms of convergence
                   speed and accuracy. We demonstrate its
                   effectiveness on a large set of indoor real-world
                   maps, and a very large simulated dataset. Open-
                   source implementations in C++, and the datasets,
                   are publicly available.}
}
@inproceedings{grisetti10icra,
  author = {G. Grisetti and R. K{\"u}mmerle and C. Stachniss and U. Frese and C. Hertzberg},
  title = {Hierarchical Optimization on Manifolds for
Online 2D and 3D Mapping},
  booktitle = {Proc. of the IEEE Int. Conf. on Robotics and
Automation (ICRA)},
  year = 2010,
  month = may,
  doi = {10.1109/ROBOT.2010.5509407},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti10icra.pdf},
  downloads = {http://www.openslam.org/hog-man.html_Open_source_implementation_-_HOG-Man},
  downloads = {http://www.openslam.org/hog-man.html_Open_source_implementation_-_HOG-Man},
  address = {Anchorage, AK, USA},
  abstract = {In this paper, we present a new hierarchical
                   optimization solution to the graph-based
                   simultaneous localization and mapping (SLAM)
                   problem. During online mapping, the approach
                   corrects only the coarse structure of the scene and
                   not the overall map. In this way, only updates for
                   the parts of the map that need to be considered for
                   making data associations are carried out. The
                   hierarchical approach provides accurate non-linear
                   map estimates while being highly efficient. Our
                   error minimization approach exploits the manifold
                   structure of the underlying space.  In this way, it
                   avoids singularities in the state space
                   parameterization.  The overall approach is
                   accurate, efficient, designed for online operation,
                   overcomes singularities, provides a hierarchical
                   representation, and outperforms a series of state-
                   of-the-art methods.}
}
@article{lau10ijsr,
  author = {Boris Lau and Kai O. Arras and Wolfram Burgard},
  title = {Multi-model Hypothesis Group Tracking and Group
Size Estimation},
  journal = {International Journal of Social Robotics, Springer},
  volume = {2},
  number = {1},
  pages = {19--30},
  year = 2010,
  url = {http://www.springerlink.com/content/gq863gk53135u1p4/}
}
@inproceedings{lau10iros,
  author = {Boris Lau and Christoph Sprunk and Wolfram Burgard},
  title = {Improved Updating of Euclidean Distance Maps
and {Voronoi} Diagrams},
  booktitle = {Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems},
  year = 2010,
  doi = {10.1109/IROS.2010.5650794},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lau10iros.pdf},
  address = {Taipei, Taiwan}
}
@inproceedings{mueller10icra,
  author = {M\"{u}ller, J. and Gonsior, C. and Burgard, W.},
  title = {Improved {M}onte {C}arlo Localization of
Autonomous Robots through Simultaneous Estimation of
Motion Model Parameters},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics \& Automation (ICRA)},
  pages = {2604-2609},
  year = 2010,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller10icra.pdf},
  address = {Anchorage, AK, USA}
}
@article{cornils10,
  author = {Cornils, M. and Rottmann, A. and Paul, O.},
  title = {How to Extract the Sheet Resistance and Hall
Mobility From Arbitrarily Shaped Planar Four-
Terminal Devices With Extended Contacts},
  journal = {IEEE Transactions on Electron Devices},
  volume = {57},
  number = {9},
  pages = {2087--2097},
  year = 2010
}
@inproceedings{rottmann10dagm,
  author = {Rottmann, A. and Burgard, W.},
  title = {Learning Non-stationary System Dynamics Online
Using {G}aussian Processes},
  booktitle = {Proc.~of the German Association for Pattern
Recognition (DAGM)},
  pages = {192--201},
  year = 2010
}
@inproceedings{schopp10sensors,
  author = {Schopp, P. and Rottmann, A. and Klingbeil, L. and Burgard, W. and Manoli, Y.},
  title = {Gaussian Process Based State Estimation for a
Gyroscope-Free IMU},
  booktitle = {Proc.~ of the IEEE Sensors Conference},
  pages = {873--878},
  year = 2010
}
@inproceedings{ruhnke10iros,
  author = {Ruhnke, M. and Steder, B. and Grisetti, G. and Burgard, W},
  title = {Unsupervised Learning of Compact 3D Models
Based on the Detection of Recurrent Structures},
  booktitle = {Proc.~of the Int.~Conf.~on Intelligent Robots
and Systems (IROS)},
  year = 2010,
  month = oct,
  doi = {10.1109/IROS.2010.5649730},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke10iros.pdf},
  address = {Taipei, Taiwan},
  abstract = {In this paper we describe a novel algorithm for
                   constructing a compact representation of 3D laser
                   range data. Our approach extracts an alphabet of
                   local scans from the scene. The words of this
                   alphabet are used to replace recurrent local 3D
                   structures and which leads to a substantial
                   compression of the entire point cloud. We optimize
                   our model in terms of complexity and accuracy by
                   minimizing the Bayesian information criterion
                   (BIC). Experimental evaluations on large real-world
                   data show that our method allows robots to
                   accurately reconstruct environments with as few as
                   70 words.}
}
@inproceedings{burgard10irosws,
  author = {Burgard, W. and Wurm, K.M. and  Bennewitz, M. and Stachniss, C. and  Hornung, A. and Rusu, R.B. and Konolige, K.},
  title = {Modeling the World Around Us: An Efficient 3D
Representation for Personal Robotics},
  booktitle = {Workshop on Defining and Solving Realistic
Perception Problems in Personal Robotics at the
IEEE/RSJ Int.~Conf.~on Intelligent Robots and
Systems},
  year = 2010,
  address = {Taipei, Taiwan}
}
@inproceedings{wurm10iros,
  author = {K.M. Wurm and C. Dornhege and P. Eyerich and C. Stachniss and  B. Nebel and W. Burgard},
  title = {Coordinated Exploration with Marsupial Teams of
Robots using Temporal Symbolic Planning},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2010,
  month = oct,
  doi = {10.1109/IROS.2010.5649820},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm10iros.pdf},
  address = {Taipei, Taiwan}
}
@inproceedings{sturm10iros,
  author = {J. Sturm and A. Jain and C. Stachniss and C.C. Kemp and W. Burgard},
  title = {Robustly Operating Articulated Objects based on
Experience},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2010,
  doi = {10.1109/IROS.2010.5653813},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm10iros.pdf},
  address = {Taipei, Taiwan}
}
@inproceedings{frank10iros,
  author = {B. Frank  and R. Schmedding and C. Stachniss and M. Teschner and W. Burgard},
  title = {Learning the Elasticity Parameters of
Deformable Objects with a Manipulation Robot},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2010,
  doi = {10.1109/IROS.2010.5653949},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank10iros.pdf},
  address = {Taipei, Taiwan}
}
@inproceedings{hornung10erlars,
  author = {A. Hornung and M.Bennewitz and C. Stachniss and H. Strasdat and S. O{\ss}wald and W. Burgard},
  title = {Learning Adaptive Navigation Strategies for
Resource-Constrained Systems},
  booktitle = {Proc.~of the Int.~Workshop on Evolutionary and
Reinforcement Learning for Autonomous Robot
Systems},
  year = 2010,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hornung10erlars.pdf},
  address = {Lisbon, Portugal}
}
@inproceedings{sturm10rssws,
  author = {J. Sturm and K. Konolige and C. Stachniss and W. Burgard},
  title = {3D Pose Estimation, Tracking and Model Learning
of Articulated Objects from Dense Depth Video using
Projected Texture Stereo},
  booktitle = {Proc.~of the Workshop RGB-D: Advanced Reasoning
with Depth Cameras at Robotics: Science and Systems
(RSS)},
  year = 2010,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm10rssws.pdf},
  address = {Zaragoza, Spain}
}
@inproceedings{frank10rssws,
  author = {B. Frank  and R. Schmedding and C. Stachniss and M. Teschner and W. Burgard},
  title = {Learning Deformable Object Models for Mobile
Robot Path Planning using Depth Cameras and a
Manipulation Robot},
  booktitle = {Proc.~of the Workshop RGB-D: Advanced Reasoning
with Depth Cameras at Robotics: Science and Systems
(RSS)},
  year = 2010,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank10rssws.pdf},
  address = {Zaragoza, Spain}
}
@article{plagemann10ras,
  author = {C. Plagemann and C. Stachniss and J. Hess and F. Endres and N. Franklin},
  title = {A Nonparametric Learning Approach to Range
Sensing from Omnidirectional Vision},
  journal = {Robotics and Autonomous Systems},
  volume = {58},
  pages = {762--772},
  year = 2010,
  issue = {6}
}
@inproceedings{karg10icra,
  author = {M. Karg and K.M. Wurm and C. Stachniss and K. Dietmayer and  W. Burgard},
  title = {Consistent Mapping of Multistory Buildings  by
Introducing Global Constraints to Graph-based
{SLAM}},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2010,
  month = may,
  doi = {10.1109/ROBOT.2010.5509977},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/karg10icra.pdf},
  address = {Anchorage, Alaska}
}
@inproceedings{sturm10icra,
  author = {J. Sturm and K. Konolige and C. Stachniss and W. Burgard},
  title = {Vision-based Detection for Learning
Articulation Models of Cabinet Doors and Drawers in
Household Environments},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2010,
  doi = {10.1109/ROBOT.2010.5509985},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm10icra.pdf},
  address = {Anchorage, Alaska}
}
@inproceedings{wurm10icraws,
  author = {K.M. Wurm and A. Hornung and M. Bennewitz and C. Stachniss and W. Burgard},
  title = {{OctoMap}: A Probabilistic, Flexible, and
Compact {3D} Map Representation for Robotic
Systems},
  booktitle = {Proc. of the ICRA 2010 Workshop on Best
Practice in 3D Perception and Modeling for Mobile
Manipulation},
  year = 2010,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm10icraws.pdf},
  address = {Anchorage, AK, USA}
}
@incollection{mueller10cogsysbook,
  author = {M\"{u}ller, J. and Stachniss, C. and Arras, K.O. and Burgard, W.},
  title = {Socially Inspired Motion Planning for Mobile
Robots in Populated Environments},
  booktitle = {Cognitive Systems},
  year = 2010,
  note = {In press},
  publisher = {Springer},
  series = {Cognitive Systems Monographs}
}
@article{wurm10ras,
  author = {Wurm, K.M. and Stachniss, C. and Grisetti, G.},
  title = {Bridging the Gap Between Feature- and Grid-
based SLAM},
  journal = {Robotics and Autonomous Systems},
  volume = {58},
  number = {2},
  pages = {140 - 148},
  year = 2010,
  doi = {10.1016/j.robot.2009.09.009},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm10ras.pdf},
  issn = {0921-8890}
}
@inproceedings{steder10irosws,
  author = {B. Steder and R. B. Rusu and K. Konolige and W. Burgard},
  title = {{NARF}: {3D} Range Image Features for Object
Recognition},
  booktitle = {Workshop on Defining and Solving Realistic
Perception Problems in Personal Robotics at the
IEEE/RSJ Int. Conf. on Intelligent Robots and
Systems (IROS)},
  year = 2010,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder10irosws.pdf},
  address = {Taipei, Taiwan},
  abstract = {We present our findings regarding a novel method
                   for interest point detection and feature descriptor
                   calculation in 3D range data called NARF~(Normal
                   Aligned Radial Feature). The method makes explicit
                   use of object boundary information and tries to
                   extract the features in areas where the surface is
                   stable but has substantial change in the
                   vicinity.}
}
@inproceedings{steder10icra,
  author = {Steder, B. and Grisetti, G. and Burgard, W.},
  title = {Robust Place Recognition for {3D} Range Data
based on Point Features},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2010,
  doi = {10.1109/ROBOT.2010.5509401},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder10icra.pdf},
  abstract = {The problem of place recognition appears in
                   different mobile robot navigation problems
                   including localization, SLAM, or change detection
                   in dynamic environments. Whereas this problem has
                   been studied intensively in the context of robot
                   vision, relatively few approaches are available for
                   three- dimensional range data.  In this paper, we
                   present a novel and robust method for place
                   recognition based on range images. Our algorithm
                   matches a given 3D scan against a database using
                   point features and scores potential transformations
                   by comparing significant points in the scans. A
                   further advantage of our approach is that the
                   features allow for a computation of the relative
                   transformations between scans which is relevant for
                   registration processes. Our approach has been
                   implemented and tested on different 3D data sets
                   obtained outdoors. In several experiments we
                   demonstrate the advantages of our approach also in
                   comparison to existing techniques.}
}
@inproceedings{hornung10iros,
  author = {Armin Hornung and Kai M. Wurm and Maren Bennewitz},
  title = {Humanoid Robot Localization in Complex Indoor
Environments},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2010,
  doi = {10.1109/IROS.2010.5649751},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hornung10iros.pdf},
  address = {Taipei, Taiwan}
}
@inproceedings{meyerdelius10iros,
  author = {D. Meyer-Delius and J. Hess and G. Grisetti and W. Burgard},
  title = {Temporary Maps for Robust Localization in Semi-static Environments},
  booktitle = {Proc.~of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year = 2010,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyerdelius10iros.pdf},
  address = {Taipei, Taiwan}
}
@inproceedings{hornung09iros,
  author = {A. Hornung and H. Strasdat and M. Bennewitz and W. Burgard},
  title = {Learning Efficient Policies for Vision-based
Navigation},
  booktitle = {Proc. of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2009,
  doi = {10.1109/IROS.2009.5354634},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/hornung09iros.pdf}
}
@inproceedings{eppner09icra,
  author = {C. Eppner and J. Sturm and M. Bennewitz and Stachniss, C. and Burgard, W.},
  title = {Imitation Learning with Generalized Task
Descriptions},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152466},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/eppner09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{pretto09icra,
  author = {A. Pretto and E. Menegatti and M. Bennewitz and W. Burgard and E. Pagello},
  title = {A Visual Odometry Framework Robust to Motion
Blur},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152447},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pretto09icra.pdf}
}
@inproceedings{bennewitz09icra,
  author = {M. Bennewitz and  Stachniss, C. and Behnke, S. and  Burgard, W.},
  title = {Utilizing Reflection Properties of Surfaces to
Improve Mobile Robot Localization},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152186},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{grzonka09icra,
  author = {Grzonka, S. and Grisetti, G. and Burgard, W.},
  title = {Towards a Navigation System for Autonomous
Indoor Flying},
  booktitle = {Proc. IEEE International Conference on Robotics
and Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152446},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{grzonka09ijrr,
  author = {Grzonka, S. and Plagemann, C. and Grisetti, G. and Burgard, W.},
  title = {Look-ahead Proposals for Robust Grid-based SLAM
with Rao-Blackwellized Particle Filters},
  booktitle = {International Journal of Robotics Research
(IJRR)},
  pages = {191-200},
  year = 2009,
  month = feb,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka09ijrr.pdf}
}
@inproceedings{joho09ecmr,
  author = {Dominik Joho and Martin Senk and Wolfram Burgard},
  title = {Learning Wayfinding Heuristics Based on Local
Information of Object Maps},
  booktitle = {Proceedings of the European Conference on
Mobile Robots {(ECMR)}},
  pages = {117--122},
  year = 2009,
  month = sep,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho09ecmr.pdf},
  isbn = {978-953-6037-54-4},
  address = {Mlini/Dubrovnik, Croatia}
}
@inproceedings{joho09icra,
  author = {Dominik Joho and Christian Plagemann and Wolfram Burgard},
  title = {Modeling {RFID} Signal Strength and Tag
Detection for Localization and Mapping},
  booktitle = {Proceedings of the {IEEE} International
Conference on Robotics and Automation {(ICRA)}},
  pages = {3160--3165},
  year = 2009,
  month = may,
  doi = {10.1109/ROBOT.2009.5152372},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho09icra.pdf},
  note = {to appear},
  isbn = {978-1-4244-2788-8},
  address = {Kobe, Japan},
  abstract = {In recent years, there has been an increasing
                   interest within the robotics community to
                   investigate if Radio Frequency Identification
                   (RFID) technology can be utilized for solving
                   localization and mapping problems in the context of
                   mobile robots. We present a novel sensor model
                   which can be utilized for localizing RFID tags and
                   for tracking a mobile agent moving through an RFID-
                   equipped environment. The proposed probabilistic
                   sensor model characterizes the received signal
                   strength indication (RSSI) information as well as
                   the tag detection events to achieve a higher
                   modeling accuracy compared to state-of-the-art
                   models that deal with one of these aspects only. We
                   furthermore propose a method that is able to
                   bootstrap such a sensor model in a fully
                   unsupervised fashion. Real- world experiments
                   demonstrate the effectiveness of the proposed
                   approach also in comparison to existing
                   techniques.},
  issn = {1050-4729}
}
@article{kuemmerle09auro,
  author = {K\"ummerle, R. and B. Steder and C. Dornhege and M. Ruhnke and G. Grisetti and C. Stachniss and A. Kleiner},
  title = {On Measuring the Accuracy of {SLAM}
Algorithms},
  journal = {Journal of Autonomous Robots},
  volume = {27},
  number = {4},
  pages = {387--407},
  year = 2009,
  doi = {10.1007/s10514-009-9155-6},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle09auro.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/slamevaluation_Evaluation_Software_and_Datasets;
http://dx.doi.org/10.1007/s10514-009-9155-6_Online_Version},
  downloads = {http://ais.informatik.uni-freiburg.de/slamevaluation_Evaluation_Software_and_Datasets;
http://dx.doi.org/10.1007/s10514-009-9155-6_Online_Version},
  abstract = {In this paper, we address the problem of creating
                   an objective benchmark for evaluating SLAM
                   approaches. We propose a framework for analyzing
                   the results of a SLAM approach based on a metric
                   for measuring the error of the corrected
                   trajectory. This metric uses only relative
                   relations between poses and does not rely on a
                   global reference frame. This overcomes serious
                   shortcomings of approaches using a global reference
                   frame to compute the error. Our method furthermore
                   allows us to compare SLAM approaches that use
                   different estimation techniques or different sensor
                   modalities since all computations are made based on
                   the corrected trajectory of the robot. We provide
                   sets of relative relations needed to compute our
                   metric for an extensive set of datasets frequently
                   used in the robotics community. The relations have
                   been obtained by manually matching laser-range
                   observations to avoid the errors caused by matching
                   algorithms. Our benchmark framework allows the user
                   to easily analyze and objectively compare different
                   SLAM approaches.},
  issue = {4}
}
@inproceedings{wurm09iros,
  author = {K.M. Wurm and R. K{\"u}mmerle and C. Stachniss and W. Burgard},
  title = {Improving Robot Navigation in Structured
Outdoor Environments by Identifying Vegetation from
Laser Data},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2009,
  month = oct,
  doi = {10.1109/IROS.2009.5354530},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm09iros.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/terrain-autonomous-msmpeg.avi_Xvid_Avi_(5_MB)},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/terrain-autonomous-msmpeg.avi_Xvid_Avi_(5_MB)},
  address = {St. Louis, MO, USA},
  abstract = {This paper addresses the problem of vegetation
                   detection from laser measurements. The ability to
                   detect vegetation is important for robots operating
                   outdoors, since it enables a robot to navigate more
                   efficiently and safely in such environments. In
                   this paper, we propose a novel approach for
                   detecting low, grass-like vegetation using laser
                   remission values. In our algorithm, the laser
                   remission is modeled as a function of distance,
                   incidence angle, and material. We classify surface
                   terrain based on 3D scans of the surroundings of
                   the robot. The model is learned in a self-
                   supervised way using vibration- based terrain
                   classification.  In all real world experiments we
                   carried out, our approach yields a classification
                   accuracy of over 99\%. We furthermore illustrate
                   how the learned classifier can improve the
                   autonomous navigation capabilities of mobile
                   robots.}
}
@inproceedings{burgard09iros,
  author = {W. Burgard and C. Stachniss and G. Grisetti and B. Steder and R. K{\"u}mmerle and C. Dornhege and M. Ruhnke and A. Kleiner and Juan D. Tard{\'o}s},
  title = {A Comparison of SLAM Algorithms Based on a
Graph of Relations},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2009,
  month = oct,
  doi = {10.1109/IROS.2009.5354691},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/burgard09iros.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/slameval-video.avi_Xvid_Avi_(3_MB)},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/slameval-video.avi_Xvid_Avi_(3_MB)},
  address = {St. Louis, MO, USA},
  abstract = {In this paper, we address the problem of creating
                   an objective benchmark for comparing SLAM
                   approaches. We propose a framework for analyzing
                   the results of SLAM approaches based on a metric
                   for measuring the error of the corrected
                   trajectory. The metric uses only relative relations
                   between poses and does not rely on a global
                   reference frame.  The idea is related to graph-
                   based SLAM approaches in the sense that it
                   considers the energy needed to deform the
                   trajectory estimated by a SLAM approach to the
                   ground truth trajectory.  Our method enables us to
                   compare SLAM approaches that use different
                   estimation techniques or different sensor
                   modalities since all computations are made based on
                   the corrected trajectory of the robot.  We provide
                   sets of relative relations needed to compute our
                   metric for an extensive set of datasets frequently
                   used in the SLAM community. The relations have been
                   obtained by manually matching laser-range
                   observations. We believe that our benchmarking
                   framework allows the user an easy analysis and
                   objective comparisons between different SLAM
                   approaches.}
}
@inproceedings{kuemmerle09rss,
  author = {K{\"u}mmerle, R. and Steder, B. and Dornhege, C. and Kleiner, A. and Grisetti, G. and Burgard, W.},
  title = {Large Scale Graph-based {SLAM} using Aerial
Images as Prior Information},
  booktitle = {Proceedings of Robotics: Science and Systems
(RSS)},
  year = 2009,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle09rss.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/satelliteSLAM_indoorFast.avi_Xvid_Avi_(53_MB)},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/satelliteSLAM_indoorFast.avi_Xvid_Avi_(53_MB)},
  address = {Seattle, WA, USA},
  abstract = {To effectively navigate in their environments and
                   accurately reach their target locations, mobile
                   robots require a globally consistent map of the
                   environment.  The problem of learning a map with a
                   mobile robot has been intensively studied in the
                   past and is usually referred to as the simultaneous
                   localization and mapping (SLAM) problem.  However,
                   existing solutions to the SLAM problem typically
                   rely on loop-closures to obtain global consistency
                   and do not exploit prior information even if it is
                   available. In this paper, we present a novel SLAM
                   approach that achieves global consistency by
                   utilizing publicly accessible aerial photographs as
                   prior information.  Our approach inserts
                   correspondences found between three-dimensional
                   laser range scans and the aerial image as
                   constraints into a graph-based formulation of the
                   SLAM problem.  We evaluate our algorithm based on
                   large real-world datasets acquired in a mixed in-
                   and outdoor environment by comparing the global
                   accuracy with state-of-the-art SLAM approaches and
                   GPS.  The experimental results demonstrate that the
                   maps acquired with our method show increased global
                   consistency.}
}
@inproceedings{kuemmerle09icra,
  author = {R. K{\"u}mmerle and D. H{\"a}hnel and D. Dolgov and S. Thrun and W. Burgard},
  title = {Autonomous Driving in a Multi-level Parking
Structure},
  booktitle = {Proc. of the IEEE Int. Conf. on Robotics and
Automation (ICRA)},
  pages = {3395--3400},
  year = 2009,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle09icra.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/stanford-parking-garage-autonomous-double.avi_Xvid_Avi_(9_MB);
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/stanford-parking-garage-autonomous-double.wmv_WMV_(11_MB)},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/stanford-parking-garage-autonomous-double.avi_Xvid_Avi_(9_MB);
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/stanford-parking-garage-autonomous-double.wmv_WMV_(11_MB)},
  address = {Kobe, Japan},
  abstract = {Recently, the problem of autonomous navigation of
                   automobiles has gained substantial interest in the
                   robotics community.  Especially during the two
                   recent DARPA grand challenges, autonomous cars have
                   been shown to robustly navigate over extended
                   periods of time through complex desert courses or
                   through dynamic urban traffic environments.  In
                   these tasks, the robots typically relied on GPS
                   traces to follow pre-defined trajectories so that
                   only local planners were required.  In this paper,
                   we present an approach for autonomous navigation of
                   cars in indoor structures such as parking garages.
                   Our approach utilizes multi-level surface maps of
                   the corresponding environments to calculate the
                   path of the vehicle and to localize it based on
                   laser data in the absence of sufficiently accurate
                   GPS information.  It furthermore utilizes a local
                   path planner for controlling the vehicle.  In a
                   practical experiment carried out with an autonomous
                   car in a real parking garage we demonstrate that
                   our approach allows the car to autonomously park
                   itself in a large-scale multi-level structure.}
}
@inproceedings{lau09icra,
  author = {Boris Lau and Kai O. Arras and Wolfram Burgard},
  title = {Tracking Groups of People with a Multi-Model
Hypothesis Tracker},
  booktitle = {International Conference on Robotics and
Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152731},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lau09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{lau09iros,
  author = {Boris Lau and Christoph Sprunk and Wolfram Burgard},
  title = {Kinodynamic Motion Planning for Mobile Robots
Using Splines},
  booktitle = {IEEE Intl. Conf. on Intelligent Robots and
Systems (IROS)},
  year = 2009,
  month = oct,
  doi = {10.1109/IROS.2009.5354805},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lau09iros.pdf},
  address = {St. Louis, MO, USA}
}
@inproceedings{meyer-delius09iros,
  author = {D. Meyer-Delius and J. Sturm and W. Burgard},
  title = {Regression-Based Online Situation Recognition
for Vehicular Traffic Scenarios},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyerdelius09iros.pdf},
  address = {St. Louis, USA}
}
@inproceedings{meyer-delius09icra,
  author = {D. Meyer-Delius and C. Plagemann and W. Burgard},
  title = {Probabilistic Situation Recognition for
Vehicular Traffic Scenarios},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2009,
  address = {Kobe, Japan}
}
@inproceedings{mueller09icra,
  author = {M\"{u}ller, J. and Rottmann, A. and Reindl, L.M. and Burgard, W.},
  title = {A Probabilistic Sonar Sensor Model for Robust
Localization of a Small-size Blimp in Indoor
Environments using a Particle Filter},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics \& Automation (ICRA)},
  pages = {3589-3594},
  year = 2009,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{meyerdelius09icra,
  author = {Daniel Meyer-Delius and Christian Plagemann and Wolfram Burgard},
  title = {Probabilistic Situation Recognition and its
Application to Vehicular Traffic Situations},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyerdelius09icra.pdf},
  note = {to appear},
  address = {Kobe, Japan},
  abstract = {To act intelligently in dynamic environments, a
                   system must understand the current situation it is
                   involved in at any given time. This requires
                   dealing with temporal context, handling multiple
                   and ambiguous interpretations, and accounting for
                   various sources of uncertainty. In this paper we
                   propose a probabilistic approach to modeling and
                   recognizing situations. We define a situation as a
                   distribution over sequences of states that have
                   some meaningful interpretation.  Each situation is
                   characterized by an individual hidden Markov model
                   that describes the corresponding distribution. In
                   particular, we consider typical traffic scenarios
                   and describe how our framework can be used to model
                   and track different situations while they are
                   evolving. The approach was evaluated experimentally
                   in vehicular traffic scenarios using real and
                   simulated data. The results show that our system is
                   able to recognize and track multiple situation
                   instances in parallel and make sensible decisions
                   between competing hypotheses. Additionally, we show
                   that our models can be used for predicting the
                   position of the tracked vehicles.}
}
@inproceedings{rottmann09icra,
  author = {Rottmann, A. and Burgard, W.},
  title = {Adaptive autonomous control using online value
iteration with {G}aussian processes},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  pages = {2106--2111},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152660}
}
@inproceedings{ruhnke09icra,
  author = {Ruhnke, M. and Steder, B. and Grisetti, G. and Burgard, W},
  title = {Unsupervised Learning of 3D Object Models from
Partial Views},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152524},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ruhnke09icra.pdf},
  address = {Kobe, Japan}
}
@phdthesis{stachniss09habil,
  author = {C. Stachniss},
  title = {Spatial Modeling and Robot Navigation},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss-habil.pdf}
}
@article{grisetti09its,
  author = {Grisetti, G. and Stachniss, C.  and Burgard, W.},
  title = {Non-linear Constraint Network Optimization for
Efficient Map Learning},
  journal = {IEEE Transactions on Intelligent
Transportation Systems},
  volume = {10},
  number = {3},
  pages = {428--439},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti09its.pdf}
}
@inproceedings{schneider09iros,
  author = {A. Schneider and J. Sturm  C. Stachniss and M. Reisert and H. Burkhardt and W. Burgard},
  title = {Object Identification with Tactile Sensors
Using Bag-of-Features},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2009,
  doi = {10.1109/IROS.2009.5354648},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm09iros.pdf}
}
@inproceedings{endres09rss,
  author = {F. Endres and C. Plagemann  and  Stachniss, C.  and  Burgard, W.},
  title = {Scene Analysis using Latent Dirichlet
Allocation},
  booktitle = {Proc.~of Robotics: Science and Systems (RSS)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres09rss-draft.pdf},
  address = {Seattle, WA, USA}
}
@inproceedings{endres09rssws,
  author = {Endres, F. and Hess, J. and Franklin, N. and Plagemann, C. and Stachniss, C. and Burgard, W.},
  title = {Estimating Range Information from Monocular
Vision},
  booktitle = {Workshop Regression in Robotics - Approaches
and Applications at Robotics: Science and Systems
(RSS)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/endres09rsswsposter.pdf},
  address = {Seattle, WA, USA}
}
@inproceedings{sturm09ijcai,
  author = {J. Sturm   and V. Predeap and  Stachniss, C. and C. Plagemann  and K. Konolige and  Burgard, W.},
  title = {Learning  Kinematic Models for Articulated
Objects},
  booktitle = {Proc.~of the Int.~Conf.~on Artificial
Intelligence (IJCAI)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm09ijcai.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{sturm09snowbird,
  author = {J. Sturm and  Stachniss, C.  and V. Predeap and C. Plagemann  and K. Konolige and  Burgard, W.},
  title = {Learning  Kinematic Models for Articulated
Objects},
  booktitle = {Online Proc. of the Learning Workshop
(Snowbird)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm09snowbird.pdf},
  address = {Clearwater, FL, USA}
}
@article{stachniss09auro,
  author = {Stachniss, C. and Plagemann, C. and Lilienthal, A.J.},
  title = {Gas Distribution Modeling using Sparse Gaussian
Process Mixtures},
  journal = {Autonomous Robots},
  volume = {26},
  pages = {187ff},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss09auro.pdf},
  issue = {2}
}
@book{stachniss09springerbook,
  author = {C. Stachniss},
  title = {Robotic Mapping and Exploration},
  volume = {55},
  year = 2009,
  publisher = {Springer},
  isbn = {978-3-642-01096-5},
  series = {STAR Springer tracts in advanced robotics}
}
@inproceedings{strasdat09icra,
  author = {H. Strasdat and  Stachniss, C. and Burgard, W.},
  title = {Which Landmark is Useful? Learning Selection
Policies for Navigation in Unknown Environments},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152207},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/strasdat09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{frank09icra,
  author = {B. Frank and C. Stachniss and R. Schmedding  and  W. Burgard and M. Teschner},
  title = {Real-world Robot Navigation amongst Deformable
Obstacles},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2009,
  doi = {10.1109/ROBOT.2009.5152275},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank09icra.pdf},
  address = {Kobe, Japan}
}
@inproceedings{steder09iros,
  author = {Steder, B. and Grisetti, G. and Van Loock, M. and Burgard, W.},
  title = {Robust On-line Model-based Object Detection
from Range Images},
  booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on
Intelligent Robots and Systems (IROS)},
  year = 2009,
  month = oct,
  doi = {10.1109/IROS.2009.5354400},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder09iros.pdf},
  address = {St. Louis, MO, USA}
}
@inproceedings{schulz09gwr,
  author = {H. Schulz and L. Ott and J. Sturm and W. Burgard},
  title = {Learning Kinematics from Direct Self-
Observation Using Nearest-Neighbor Methods},
  booktitle = {Proc.~of the German Workshop on Robotics},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/schulz09gwr.pdf}
}
@inproceedings{sturm09rssws,
  author = {J. Sturm and C. Stachniss and V. Pradeep and C. Plagemann and K. Konolige and W. Burgard},
  title = {Towards Understanding Articulated Objects},
  booktitle = {Proc.~of the Workshop on Robot Manipulation at
Robotics: Science and Systems Conference (RSS)},
  year = 2009,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm09rss-manip.pdf},
  address = {Seattle, WA, USA}
}
@article{sturm09jp,
  author = {J. Sturm and C. Plagemann and W. Burgard},
  title = {Body schema learning for robotic manipulators
from visual self-perception},
  journal = {Journal of Physiology-Paris},
  volume = {103},
  number = {3-5},
  pages = {220--231},
  year = 2009,
  doi = {DOI: 10.1016/j.jphysparis.2009.08.005},
  url = {http://www.sciencedirect.com/science/article/B6VMC-4WY6JVM-D/2/0aaabe9b7dc9628c8c818fa87c8b56e9},
  note = {Neurorobotics},
  issn = {0928-4257}
}
@phdthesis{mozos2008phd,
  author = {Oscar Martinez Mozos},
  title = {Semantic Place Labeling with Mobile Robots},
  school = {University of Freiburg},
  year = 2008,
  month = jul,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mozos2008phd.pdf},
  category = {thesis},
  address = {Freiburg, Germany}
}
@article{zender2008ras,
  author = {Hendrik Zender and Oscar Martinez Mozos and Patric Jensfelt and  Geert-Jan M. Kruijff and Wolfram Burgard},
  title = {Conceptual Spatial Representations for Indoor
Mobile Robots},
  journal = {Robotics and Autonomous Systems},
  volume = {56},
  number = {6},
  pages = {493--502},
  year = 2008,
  month = jun,
  doi = {10.1016/j.robot.2008.03.007},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/zender2008ras.pdf},
  category = {journal},
  publisher = {Elsevier},
  jcr = {0.832 (2006)},
  position = {4/12 ROBOTICS (2006)},
  issn = {0921-8890}
}
@article{stachniss09amai,
  author = {Cyrill Stachniss and Oscar Martinez Mozos and Wolfram Burgard},
  title = {Efficient Exploration of Unknown Indoor
Environments using a Team of Mobile Robots},
  journal = {Annals of Mathematics and Artificial
Intelligence},
  volume = {52},
  pages = {205ff},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss09amai.pdf},
  category = {journal},
  note = {To appear},
  jcr = {0.756 (2007)},
  issn = {1012-2443},
  issue = {2}
}
@inproceedings{pronobis2008icra,
  author = {Pronobis, A. and Martinez Mozos, O. and Caputo, B.},
  title = {{SVM}-based Discriminative Accumulation Scheme
for Place Recognition},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics and Automation},
  pages = {522--529},
  year = 2008,
  month = may,
  doi = {10.1109/ROBOT.2008.4543260},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pronobis2008icra.pdf},
  category = {conference},
  isbn = {978-1-4244-1647-9},
  address = {Pasadena, CA, USA},
  issn = {1050-4729}
}
@inbook{triebel2007gfkl_b,
  author = {Triebel, R. and Mozos, O.M. and Burgard, W.},
  title = {Studies in Classification, Data Analysis, and
Knowledge Organization},
  pages = {293--300},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/triebel2007gfkl_book.pdf},
  chapter = {Relational Learning in Mobile Robotics: An
                   Application to Semantic Labeling of Objects in {2D}
                   and {3D} Environment Maps},
  publisher = {Springer-Verlag},
  editor = {C. Preisach, H. Burkhardt, L.Schmidt-Thieme,
                   R.Decker},
  category = {book_chapter}
}
@inproceedings{axenbeck08humanoids,
  author = {T. Axenbeck and M. Bennewitz and S. Behnke and W. Burgard},
  title = {Recognizing Complex, Parameterized Gestures
from Monocular Image Sequences},
  booktitle = {Proc.~of the IEEE-RAS International Conference
on Humanoid Robots (Humanoids)},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/axenbeck08humanoids.pdf}
}
@inproceedings{stachniss08icra,
  author = {Stachniss, C. and Bennewitz, M. and Grisetti, G. and Behnke, S. and Burgard, W.},
  title = {How to Learn Accurate Grid Maps with a
Humanoid},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543697},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss08icra.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{bennewitz08rssws,
  author = {M. Bennewitz and T. Axenbeck and S. Behnke and W. Burgard},
  title = {Robust Recognition of Complex Gestures for
Natural Human-Robot Interaction},
  booktitle = {Proc. of the Workshop on Interactive Robot
Learning at Robotics: Science and Systems Conference
(RSS)},
  year = 2008
}
@inproceedings{grzonka08simpar,
  author = {Grzonka, S. and Grisetti, G. and Burgard, W.},
  title = {Autonomous Indoors Navigation using a Small-
Size Quadrotor},
  booktitle = {Workshop Proc. of Intl. Conf. on Simulation, Modeling and Programming for Autonomous Robots
(SIMPAR)},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka08simpar.pdf},
  address = {Venice, Italy}
}
@inproceedings{grzonka08iros,
  author = {Grzonka, S. and Bouabdallah, S. and Grisetti, G. and Burgard, W. and Siegwart, R.},
  title = {Towards a Fully Autonomous Indoor Helicopter},
  booktitle = {Workshop of IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka08irosWS.pdf},
  address = {Nice, France}
}
@inproceedings{arras08icra,
  author = {Arras, K. and Grzonka, S. and Luber, M. and Burgard, W.},
  title = {Efficient People Tracking in Laser Range Data
using a Multi-Hypothesis Leg-Tracker with Adaptive
Occlusion Probabilities},
  booktitle = {Proc. IEEE International Conference on Robotics
and Automation (ICRA)},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543447},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/arras08icra.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{steder08visapp,
  author = {Steder, B. and Grisetti, G. and Grzonka, S. and Stachniss, C. and Burgard, W.},
  title = {Estimating Consistent Elevation Maps using
Down-Looking Cameras and Inertial Sensors},
  booktitle = {Proc. of the Workshop on Robotic Perception on
the International Conference on Computer Vision
Theory and Applications},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder08visapp.pdf},
  address = {Funchal, Madeira, Portugal}
}
@inproceedings{kretzschmar08iros,
  author = {Henrik Kretzschmar and Cyrill Stachniss and Christian Plagemann and Wolfram Burgard},
  title = {Estimating Landmark Locations from Geo-
Referenced Photographs},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  pages = {2902--2907},
  year = 2008,
  doi = {10.1109/IROS.2008.4650855},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kretzschmar08iros.pdf},
  optpdfurl = {http://ais.informatik.uni-freiburg.de/publications/papers/.pdf},
  address = {Nice, France},
  abstract = {}
}
@article{kuemmerle08jfr,
  author = {K{\"u}mmerle, R. and Triebel, R. and Pfaff, P. and Burgard, W.},
  title = {Monte Carlo Localization in Outdoor Terrains
using Multilevel Surface Maps},
  journal = {Journal of Field Robotics (JFR)},
  volume = {25},
  pages = {346--359},
  year = 2008,
  month = {June - July},
  doi = {10.1002/rob.20245},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle08jfr.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie_sbahn.avi_Xvid_Avi_(15_MB);
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie-79er.avi_Xvid_Avi_(19_MB)},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie_sbahn.avi_Xvid_Avi_(15_MB);
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie-79er.avi_Xvid_Avi_(19_MB)},
  abstract = {We propose a novel combination of techniques for
                   robustly estimating the position of a mobile robot
                   in outdoor environments using range data. Our
                   approach applies a particle filter to estimate the
                   full six-dimensional state of the robot and
                   utilizes multilevel surface maps, which, in
                   contrast to standard elevation maps, allow the
                   robot to represent vertical structures and multiple
                   levels in the environment. We describe
                   probabilistic motion and sensor models to calculate
                   the proposal distribution and to evaluate the
                   likelihood of observations. We furthermore describe
                   an active localization approach that actively
                   selects the sensor orientation of the two-
                   dimensional laser range scanner to improve the
                   localization results. To efficiently calculate the
                   appropriate orientation, we apply a clustering
                   operation on the particles and evaluate potential
                   orientations on the basis of these clusters.
                   Experimental results obtained with a mobile robot
                   in large-scale outdoor environments indicate that
                   our approach yields robust and accurate position
                   estimates. The experiments also demonstrate that
                   multilevel surface maps lead to a significantly
                   better localization performance than standard
                   elevation maps. They additionally show that further
                   accuracy is obtained from the active sensing
                   approach.}
}
@inproceedings{mueller08cogsys,
  author = {M\"{u}ller, J. and Stachniss, C. and Arras, K.O. and Burgard, W.},
  title = {Socially Inspired Motion Planning for Mobile
Robots in Populated Environments},
  booktitle = {Proceedings of the International Conference on
Cognitive Systems (CogSys)},
  pages = {85-90},
  year = 2008,
  month = apr,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mueller08cogsys.pdf},
  address = {Karlsruhe, Germany}
}
@inproceedings{pfaff08icra,
  author = {Patrick Pfaff and Christian Plagemann and Wolfram Burgard},
  title = {Gaussian Mixture Models for Probabilistic
Localization},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543251},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pfaff08icra.pdf},
  note = {to appear},
  address = {Pasadena, CA, USA},
  abstract = {Range sensors have become popular for mobile robot
                   localization since they directly measure the
                   geometry of the local environment. In situations in
                   which the robot operates close to obstacles or in
                   highly cluttered environments, however, small
                   changes in the pose of the robot can lead to
                   completely different geometries measured by the
                   range sensor. The resulting enormous variances in
                   the likelihood of observations can lead to major
                   problems in probabilistic approaches such as Monte
                   Carlo localization as important hypotheses or
                   particles might get lost which substantially
                   decreases the robustness of such approaches. A
                   common solution is to artificially smooth the
                   likelihood function or to only integrate a small
                   fraction of the measurements. In this paper we
                   present a more fundamental and robust approach
                   which models the likelihood function for single
                   range measurements as a mixture of Gaussians. In
                   practical experiments we compare our approach to
                   previous methods and demonstrate that it provides a
                   substantially more robust localization.}
}
@inproceedings{pfaff08iros,
  author = {P. Pfaff and C. Stachniss and C. Plagemann and W. Burgard},
  title = {Efficiently Learning High-dimensional
Observation Models for Monte-Carlo Localization
using Gaussian Mixtures},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2008,
  doi = {10.1109/IROS.2008.4650711},
  url = {http://ais.informatik.uni-freiburg.de/~stachnis/pdf/pfaff08iros.pdf},
  address = {Nice, France},
  abstract = {Whereas probabilistic approaches are a powerful
                   tool for mobile robot localization, they heavily
                   rely on the proper definition of the so-called
                   observation model which defines the likelihood of
                   an observation given the position and orientation
                   of the robot and the map of the environment. Most
                   of the sensor models for range sensors proposed in
                   the past either consider the individual beam
                   measurements independently or apply uni-modal
                   models to represent the likelihood function. In
                   this paper we present an approach that learns
                   place-dependent sensor models for entire range
                   scans using Gaussian mixture models. To deal with
                   the high dimensionality of the measurement space,
                   we utilize principle component analysis for
                   dimensionality reduction. In practical experiments
                   carried out with data obtained from a real robot we
                   demonstrate that our model substantially
                   outperforms existing and popular sensor models.}
}
@phdthesis{plagemann08phd,
  author = {Plagemann, C.},
  title = {Gaussian Processes for Flexible Robot
Learning},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2008,
  month = dec,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann08phd.pdf}
}
@inproceedings{plagemann08ecml,
  author = {Plagemann, C. and Kersting, K. and Burgard, W.},
  title = {Nonstationary Gaussian Process Regression using
Point Estimates of Local Smoothness},
  booktitle = {Proc.~of the European Conference on Machine
Learning (ECML)},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann08ecml.pdf},
  address = {Antwerp, Belgium},
  abstract = {Gaussian processes using nonstationary covariance
                   functions are a powerful tool for Bayesian
                   regression with input-dependent smoothness. A
                   common approach is to model the local smoothness by
                   a latent process that is integrated over using
                   Markov chain Monte Carlo approaches. In this paper,
                   we demonstrate that an approximation that uses the
                   estimated mean of the local smoothness yields good
                   results and allows one to employ efficient
                   gradient- based optimization techniques for jointly
                   learning the parameters of the latent and the
                   observed processes. Extensive experiments on both
                   synthetic and real-world data, including
                   challenging problems in robotics, show the
                   relevance and feasibility of our approach.}
}
@proceedings{burgard08ias,
  title = {Proc. of the 10th International Conference on
Intelligent Autonomous Systems, Baden-Baden, Germany, July 23-25, 2008},
  booktitle = {IAS},
  year = 2008,
  publisher = {IOS Press},
  isbn = {978-1-58603-887-8},
  editor = {Burgard, W. and Dillmann, R. and Plagemann, C. and
                   Vahrenkamp, N.}
}
@inproceedings{plagemann08iros,
  author = {Plagemann, C. and Mischke, S. and Prentice, S. and Kersting, K. and Roy, N. and Burgard, W.},
  title = {Learning Predictive Terrain Models for Legged
Robot Locomotion},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2008,
  doi = {10.1109/IROS.2008.4651026},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann08iros.pdf},
  address = {Nice, France},
  abstract = {Legged robots require the ability to build
                   accurate models of their environment in order to
                   plan and execute their actions. We present a novel,
                   probabilistic terrain model based on Gaussian
                   processes that can be learned and updated
                   efficiently using sparse approximation techniques.
                   The major benefit of our model is its ability to
                   predict elevations at unseen locations more
                   reliably than alternative approaches, while it also
                   yields estimates of the predictive uncertainties.
                   In particular, our Gaussian process adapts its
                   covariance to the situation at hand, allowing more
                   accurate inference of terrain height at points that
                   have not been directly observed. We show how a
                   conventional motion planner can use the learned
                   terrain model to to plan a path to a goal location,
                   using a terrain-specific cost model to accept or
                   reject candidate footholds. In experiments with a
                   real quadruped robot equipped with a laser range
                   finder, we demonstrate the usefulness of our
                   approach and discuss its benefits compared to
                   simpler terrain models such as elevations grids.}
}
@inproceedings{stachniss08rss,
  author = {Stachniss, C. and Plagemann, C. and Lilienthal, A. and Burgard, W.},
  title = {Gas Distribution Modeling Using Sparse Gaussian
Process Mixture Models},
  booktitle = {Robotics: Science and Systems (RSS)},
  year = 2008,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss08rss.pdf},
  optpdfurl = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss08rss.pdf},
  note = {To appear},
  optabstract = {},
  address = {Zurich, Switzerland}
}
@inproceedings{luber08rss,
  author = {Luber, M. and Arras, K. and Plagemann, C. and Burgard, W.},
  title = {Tracking and Classification of Dynamic Objects:
An Unsupervised Learning Approach},
  booktitle = {Robotics: Science and Systems (RSS)},
  year = 2008,
  month = jun,
  optabstract = {},
  address = {Zurich, Switzerland}
}
@inproceedings{reiser08robotik,
  author = {Reiser, U. and Mies, C. and Plagemann, C.},
  title = {Verteilte Software-Entwicklung in der Robotik -
ein Integrations- und Testframework},
  booktitle = {Robotik},
  year = 2008,
  note = {In German},
  optmonth = {},
  address = {Munich, Germany},
  abstract = {Eine der grten Herausforderungen innerhalb der
                   Robotik ist die Integration vieler, komplexer
                   Hardware- und Softwarekomponenten zu einem robust
                   funktionierenden Gesamtsystem. Neben den
                   zahlreichen wissenschaftlichen Fragestellungen, die
                   auf Systemebene zu lsen sind, hngt der
                   Integrationserfolg insbesondere von der Lsung
                   praktischer Probleme wie dem Zusammenspiel vieler
                   Entwicklungspartner und der typischerweise stark
                   limitierten Verfgbarkeit von Einzelkomponenten ab.
                   Leistungsfhige Hardwarekomponenten, wie
                   beispielsweise Mehrfingergreifer und Leichtbauarme,
                   sind in der Regel Spezialanfertigungen und stehen
                   daher nur wenigen Partnern innerhalb von Projekten
                   zur Verfgung. In diesem Beitrag wird ein neues
                   Integrations- und Testframework zur rumlich
                   verteilten Forschung und Entwicklung an solchen
                   Komponenten und integrierten Systemen vorgestellt.
                   Entwickler knnen hierbei Beitrge zu einer
                   Technologieplattform leisten, ohne stndigen,
                   direkten Zugang zur Hardware besitzen zu mssen.}
}
@inproceedings{plagemann08icra,
  author = {Plagemann, C. and Endres, F. and Hess, J. and Stachniss, C. and Burgard, W.},
  title = {Monocular Range Sensing: A Non-Parametric
Learning Approach},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543324},
  url = {http://ais.informatik.uni-freiburg.de/~stachnis/pdf/plagemann08icra.pdf},
  address = {Pasadena, CA, USA},
  abstract = {For many applications, mobile robots need to
                   estimate the geometry of their local surrounding
                   area.  To do so, proximity sensor such as laser
                   range finders or sonars are typically employed.
                   Cameras are a cheap and lightweight alternative to
                   such sensors, but do not offer proximity
                   information directly.  In this paper, we present a
                   novel approach to learning the relationship between
                   range measurements and visual features extracted
                   from a single monocular camera image.  As the
                   learning engine, we apply Gaussian processes, a
                   non- parametric learning technique that not only
                   yields the most likely range prediction
                   corresponding to a certain visual input but also
                   the predictive uncertainty.  This information, in
                   turn, can be utilized in an extended grid-based
                   mapping scheme to update a model of the environment
                   more gently where the predictions are unreliable.
                   In practical experiments carried out with a mobile
                   robot equipped with an omnidirectional camera
                   system in different environments, we show that our
                   system is able to predict range scans accurate
                   enough to construct maps of the environment.}
}
@inproceedings{wurm08iros,
  author = {K.M. Wurm and Stachniss, C. and W. Burgard},
  title = {Coordinated  Multi-Robot Exploration using a
Segmentation of the Environment},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2008,
  month = sep,
  doi = {10.1109/IROS.2008.4650734},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm08iros.pdf},
  address = {Nice, France}
}
@inproceedings{grisetti08icra,
  author = {Grisetti, G. and Lordi Rizzini, D. and Stachniss, C. and Olson, E. and Burgard, W.},
  title = {Online Constraint Network Optimization for
Efficient Maximum Likelihood Map Learning},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543481},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti08icra.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{frank08icra,
  author = {Frank, B. and Becker, M. and Stachniss, C. and Teschner, M. and Burgard, W.},
  title = {Efficient Path Planning for Mobile Robots in
Environments with Deformable Objects},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543784},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank08icra.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{frank08icraws,
  author = {Frank, B. and Becker, M. and Stachniss, C. and Teschner, M. and Burgard, W.},
  title = {Learning Cost Functions for Mobile Robot
Navigation in Environments with Deformable Objects},
  booktitle = {Workshop on Path Planning on Cost Maps at the
IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2008,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/frank08icraws.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{steder08visappws,
  author = {Steder, B. and Grisetti, G. and Stachniss, C. and  Burgard, W.},
  title = {Learning Visual Maps using Cameras and Inertial
Sensors},
  booktitle = {Workshop on Robotic Perception, International
Conference on Computer Vision Theory and
Applications},
  year = 2008,
  note = {To appear},
  address = {Funchal, Madeira, Portugal}
}
@book{rss07proceedings,
  title = {Robotics: Science and Systems III},
  year = 2008,
  month = mar,
  note = {In press},
  publisher = {MIT Press},
  isbn = {0262524848},
  editor = {Burgard, W. and Brock, O. and Stachniss, C.}
}
@article{steder08tro,
  author = {Steder, B. and Grisetti, G. and Stachniss, C. and Burgard, W.},
  title = {Visual {SLAM} for Flying Vehicles},
  journal = {{IEEE} Transactions on Robotics},
  volume = {24},
  number = {5},
  pages = {1088--1093},
  year = 2008,
  month = nov,
  doi = {10.1109/TRO.2008.2004521},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder08tro.pdf}
}
@inproceedings{sturm08icra,
  author = {J. Sturm and C. Plagemann and W. Burgard},
  title = {Unsupervised Body Scheme Learning through Self-
Perception},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  pages = {3328--3333},
  year = 2008,
  doi = {10.1109/ROBOT.2008.4543718},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm08icra.pdf},
  address = {Pasadena, CA, USA}
}
@inproceedings{sturm08rss,
  author = {J. Sturm and C. Plagemann and W. Burgard},
  title = {Adaptive Body Scheme Models for Robust Robotic
Manipulation},
  booktitle = {Robotics: Science and Systems (RSS)},
  year = 2008,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm08rss.pdf},
  address = {Zurich, Switzerland}
}
@inproceedings{sturm08rss-workshop,
  author = {J. Sturm and C. Plagemann and W. Burgard},
  title = {Body Scheme Learning and Life-Long Adaptation
for Robotic Manipulation},
  booktitle = {Proceedings of the Workshop on Robot
Manipulation at Robotics: Science and Systems
Conference (RSS)},
  year = 2008,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sturm08rss-workshop.pdf},
  address = {Zurich, Switzerland}
}
@inproceedings{mozos2007iros_workshop,
  author = {Oscar Martinez Mozos and Patric Jensfelt and Hendrik Zender and Geert-Jan M. Kruijff and Wolfram Burgard},
  title = {From Labels to Semantics: An Integrated System
for Conceptual  Spatial Representations of Indoor
Environments for Mobile Robots},
  booktitle = {Proceedings of the IEEE/RSJ IROS 2007 Workshop:
Semantic information in robotics},
  year = 2007,
  url = {http://www2.informatik.uni-freiburg.de/~omartine/publications/mozos2007iros_workshop.html},
  googlevideo = {http://www2.informatik.uni-freiburg.de/~omartine/publications/mozos2007iros_workshop.html#video},
  category = {workshop},
  address = {San Diego, CA, USA}
}
@article{stachniss07it,
  author = {Cyrill Stachniss and Giorgio Grisetti and Oscar Martinez Mozos and Wolfram Burgard},
  title = {Efficiently Learning Metric and Topological
Maps with Autonomous Service Robots},
  journal = {it--Information Technology},
  volume = {49},
  number = {4},
  pages = {232--237},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss2007it.pdf},
  category = {journal},
  journallink = {http://it-information-technology.de/},
  editor = {Buss, M. and Lawitzki, G.},
  issn = {1611--2776}
}
@inproceedings{zender2007aaai,
  author = {Hendrik Zender and Patric Jensfelt and Oscar Martinez Mozos and Geert-Jan M. Kruijff and Wolfram Burgard},
  title = {An Integrated Robotic System for Spatial
Understanding and Situated Interaction in Indoor
Environments},
  booktitle = {Proceedings of the Conference on Artificial
Intelligence},
  year = 2007,
  url = {http://www2.informatik.uni-freiburg.de/~omartine/publications/zender2007aaai.html},
  googlevideo = {http://www2.informatik.uni-freiburg.de/~omartine/publications/zender2007aaai.html#video},
  category = {conference},
  address = {Vancouver, British Columbia, Canada}
}
@inproceedings{triebel2007gfkl,
  author = {Rudolph Triebel and Oscar Martinez Mozos and Wolfram Burgard},
  title = {Relational Learning in Mobile Robotics: An
Application to Semantic Labeling of Objects in {2D}
and {3D} Environment Maps},
  booktitle = {Annual Conference of the German Classification
Society on Data Analysis, Machine Learning, and
Applications},
  year = 2007,
  category = {conference},
  address = {Freiburg, Germany}
}
@inproceedings{mozos2007icra_workshop,
  author = {Oscar Martinez Mozos and Patric Jensfelt and Hendrik Zender and Geert-Jan M. Kruijff and Wolfram Burgard},
  title = {From Labels to Semantics: An Integrated System
for Conceptual  Spatial Representations of Indoor
Environments for Mobile Robots},
  booktitle = {Proceedings of the IEEE ICRA Workshop: Semantic
information in robotics},
  pages = {33--40},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/~omartine/publications/mozos2007icra_workshop.html},
  googlevideo = {http://ais.informatik.uni-freiburg.de/~omartine/publications/mozos2007icra_workshop.html#video},
  category = {workshop}
}
@inproceedings{arras2007icra,
  author = {Kai O. Arras and Oscar Martinez Mozos and Wolfram Burgard},
  title = {Using Boosted Features for the Detection of
People in {2D} Range Data},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics and Automation},
  pages = {3402--3407},
  year = 2007,
  doi = {10.1109/ROBOT.2007.363998},
  url = {http://ais.informatik.uni-freiburg.de/~omartine/publications/arras2007icra.html},
  video = {http://ais.informatik.uni-freiburg.de/~omartine/multimedia/AdaBoostOffice.avi},
  category = {conference}
}
@article{mozos2007ras,
  author = {Oscar Martinez Mozos and Rudolph Triebel and Patric Jensfelt and Axel Rottmann and Wolfram Burgard},
  title = {Supervised semantic labeling of places using
information extracted from sensor data},
  journal = {Robotics and Autonomous Systems},
  volume = {55},
  number = {5},
  pages = {391--402},
  year = 2007,
  month = may,
  url = {http://ais.informatik.uni-freiburg.de/~rottmann/publication/mozos07ras.pdf},
  category = {journal},
  jcr = {(0.832 2006)},
  position = {4/12 ROBOTICS (2006)}
}
@inproceedings{triebel2007ijcai,
  author = {Rudolph Triebel and Richard Schmidt and Oscar Martinez Mozos and Wolfram Burgard},
  title = {Instace-based AMN Classification for Improved
Object Recognition in 2D and 3D Laser Range Data},
  booktitle = {Proceedings of the International Joint
Conference on Artificial Intelligence},
  pages = {2225--2230},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/triebel2007ijcai.pdf},
  category = {conference},
  address = {Hyderabad, India}
}
@inbook{mozos2007star,
  author = {Oscar Martinez Mozos and Cyrill Stachniss and Axel Rottmann and Wolfram Burgard},
  title = {Robotics Research: Results of the 12th
International Symposium ISRR.},
  volume = {28},
  pages = {453--472},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mozos2007star.pdf},
  chapter = {Using AdaBoost for Place Labeling and Topological
                   Map Building.},
  publisher = {Springer-Verlag Berlin Heidelberg, Germany},
  editor = {Thrun, S. and Brooks, R. and Durrant-Whyte, H.},
  series = {{STAR} Springer tracts in advanced robotics},
  category = {book_chapter}
}
@inproceedings{strasdat07ams,
  author = {Strasdat, H. and Stachniss, C. and Bennewitz, M. and Burgard, W.},
  title = {Visual Bearing-Only Simultaneous Localization
and Mapping with Improved Feature Matching},
  booktitle = {Proc.~of the Fachgespr{\"a}che Autonome Mobile
Systeme (AMS)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/strasdat07ams.pdf},
  address = {Kaiserslautern, Germany}
}
@inproceedings{grisetti07iros,
  author = {Grisetti, G. and Grzonka, S. and Stachniss, C. and Pfaff, P. and  Burgard, W.},
  title = {Efficient Estimation of Accurate Maximum
Likelihood Maps in 3D},
  booktitle = {IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS)},
  year = 2007,
  doi = {10.1109/IROS.2007.4399030},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti07iros.pdf},
  address = {San Diego, CA, USA}
}
@inproceedings{steder07iros,
  author = {Steder, S. and Grisetti, G. and Stachniss, C. and Grzonka, S. and Rottmann, A. and  Burgard, W.},
  title = {Learning Maps in 3D using Attitude and Noisy
Vision Sensors},
  booktitle = {IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS)},
  pages = {644--649},
  year = 2007,
  doi = {10.1109/IROS.2007.4399414},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder07iros.pdf},
  address = {San Diego, CA, USA}
}
@inproceedings{grzonka07fsr,
  author = {Grzonka, S. and Plagemann, C. and Grisetti, G. and Burgard, W.},
  title = {Look-ahead Proposals for Robust Grid-based
SLAM},
  booktitle = {Proc. of the International Conference on Field
and Service Robotics (FSR)},
  year = 2007,
  month = jul,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grzonka07fsr.pdf},
  address = {Chamonix, France},
  abstract = {Simultaneous Localization and Mapping (SLAM) is
                   one of the classical problems in mobile robotics.
                   The task is to build a map of the environment using
                   on-board sensors while at the same time localizing
                   the robot relative to this map. Rao-Blackwellized
                   particle filters have emerged as a powerful
                   technique for solving the SLAM problem in a wide
                   variety of environments. It is a well-known fact
                   for sampling-based approaches that the choice of
                   the proposal distribution greatly influences the
                   robustness and efficiency achievable by the
                   algorithm. In this paper, we present a
                   significantly improved proposal distribution for
                   grid-based SLAM, which utilizes whole sequences of
                   sensor measurements rather than only the most
                   recent one. We have implemented our system on a
                   real robot and evaluated its performance on
                   standard data sets as well as in hard outdoor
                   settings with few and ambiguous features. Our
                   approach improves the localization accuracy and the
                   map quality. At the same time, it substantially
                   reduces the risk of mapping failures.}
}
@inproceedings{grisetti07rss,
  author = {Grisetti, G. and  Stachniss, C. and Grzonka, S. and Burgard},
  title = {A Tree Parameterization for Efficiently
Computing Maximum Likelihood Maps using Gradient
Descent},
  booktitle = {Proc.~of Robotics: Science and Systems (RSS)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti07rss.pdf},
  address = {Atlanta, GA, USA}
}
@inproceedings{pfaff07irosws,
  author = {Patrick Pfaff and Rainer K\"{u}mmerle and Dominik Joho and Cyrill Stachniss and Rudolph Triebel and Wolfram Burgard},
  title = {Navigation in Combined Outdoor and Indoor
Environments using Multi-Level Surface Maps},
  booktitle = {Proc. of the Workshop on Safe Navigation in
Open and Dynamic Environments at the {IEEE} Int.
Conf. on Intelligent Robots and Systems {(IROS)}},
  year = 2007,
  month = oct,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pfaff07irosws.pdf},
  address = {San Diego, CA, USA},
  abstract = {Whenever mobile robots are used in real world
                   applications, the ability to learn an accurate
                   model of the environment and to localize itself
                   based on such a model are important prerequisites
                   for reliable operation. Whereas these problems have
                   been successfully solved in the past for most
                   indoor tasks, in which the robot is assumed to
                   operate on a flat surface, such approaches are
                   likely to fail in combined indoor and outdoor
                   environments in which the three-dimensional
                   structure of the world needs to be considered. In
                   this paper, we consider the problem of localizing a
                   vehicle that operates in 3D indoor as well as
                   outdoor settings. Our approach is entirely
                   probabilistic and does not rely on GPS information.
                   It is based on so-called multi-level surface maps
                   which are an extension of the well- known elevation
                   maps. In addition to that, we present a technique
                   that allows the robot to actively explore the
                   environment. This algorithm applies a decision-
                   theoretic approach and considers the uncertainty in
                   the model to determine the next action to be
                   executed. In practical experiments, we illustrate
                   the properties as well as advantages of our
                   approach compared to other techniques.}
}
@inproceedings{joho07ams,
  author = {Dominik Joho and Cyrill Stachniss and Patrick Pfaff and Wolfram Burgard},
  title = {Autonomous Exploration for 3{D} Map Learning},
  booktitle = {{A}utonome {M}obile {S}ysteme {(AMS)}},
  pages = {22--28},
  year = 2007,
  month = oct,
  doi = {10.1007/978-3-540-74764-2_4},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho07ams.pdf},
  publisher = {Springer},
  isbn = {978-3-540-74763-5},
  editor = {Karsten Berns and Tobias Luksch},
  address = {Kaiserslautern, Germany}
}
@mastersthesis{joho07diplom,
  author = {Dominik Joho},
  title = {{E}xploration f\"{u}r mobile {R}oboter unter
{V}erwendung dreidimensionaler {U}mgebungsmodelle},
  school = {Albert-Ludwigs-Universit\"{a}t Freiburg},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/joho07diplom.pdf}
}
@inproceedings{kuemmerle07ams,
  author = {K{\"u}mmerle, R. and Pfaff, P. and Triebel, R. and Burgard, W.},
  title = {Active Monte Carlo Localization in Outdoor
Terrains using Multi-Level Surface Maps},
  booktitle = {Fachgespr{\"a}ch Autonome Mobile Systeme
(AMS)},
  pages = {22--28},
  year = 2007,
  month = oct,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle07ams.pdf},
  publisher = {Springer},
  isbn = {978-3-540-74763-5},
  editor = {Karsten Berns and Tobias Luksch},
  address = {Kaiserslautern, Germany},
  abstract = {Abstract. In this paper we consider the problem of
                   active mobile robot localization with range sensors
                   in outdoor environments. In contrast to passive
                   approaches our approach actively selects the
                   orientation of the laser range finder to improve
                   the localization results. It applies a particle
                   filter to estimate the full six- dimensional state
                   of the robot. To represent the environment we
                   utilize multi-level surface maps which allow the
                   robot to represent vertical structures and multiple
                   levels. To efficiently calculate the optimal
                   orientation for the range scanner, we apply a
                   clustering operation on the particles and only
                   evaluate potential orientations based on these
                   clusters. Experimental results obtained with a
                   mobile robot in an outdoor environment indicate
                   that the active control of the range sensor leads
                   to more efficient localization results.}
}
@inproceedings{kuemmerle07fsr,
  author = {K{\"u}mmerle, R. and Triebel, R. and Pfaff, P. and Burgard, W.},
  title = {Monte Carlo Localization in Outdoor Terrains
using Multi-Level Surface Maps},
  booktitle = {Proc. of the International Conference on Field
and Service Robotics (FSR)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kuemmerle07fsr.pdf},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie_sbahn.avi_Xvid_Avi_(15_MB);
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie-79er.avi_Xvid_Avi_(19_MB)},
  downloads = {http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie_sbahn.avi_Xvid_Avi_(15_MB);
http://ais.informatik.uni-freiburg.de/~kuemmerl/data/movie-79er.avi_Xvid_Avi_(19_MB)},
  address = {Chamonix, France},
  abstract = {In this paper we consider the problem of mobile
                   robot localization with range sensors in outdoor
                   environments.  Our approach applies a particle
                   filter to estimate the full six-dimensional state
                   of the robot.  To represent the environment we
                   utilize multi-level surface maps which allow the
                   robot to represent vertical structures and multiple
                   levels in the environment.  We describe
                   probabilistic motion and sensor models to calculate
                   the proposal distribution and to evaluate the
                   likelihood of observations.  Experimental results
                   obtained with a mobile robot in an outdoor
                   environment indicate that our approach can be used
                   to robustly and accurately localize an outdoor
                   vehicle.  The experiments also demonstrate that
                   multi-level surface maps lead to a significantly
                   better localization performance than standard
                   elevation maps.}
}
@inproceedings{meyer-delius07ecmr,
  author = {D. Meyer-Delius and W. Burgard},
  title = {Maximum-Likelihood Sample-Based Maps for Mobile
Robots},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  year = 2007,
  address = {Freiburg, Germany}
}
@inproceedings{meyer-delius07gfki,
  author = {D. Meyer-Delius and C. Plagemann and G. von Wichert and W. Feiten and G. Lawitzky and W. Burgard},
  title = {A Probabilistic Relational Model for
Characterizing Situations in Dynamic Multi-Agent
Systems},
  booktitle = {In Proc.~of the 31th Annual Conference of the
German Classification Society on Data Analysis, Machine Learning, and Applications (GFKL)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meyerdelius07gfkl.pdf},
  address = {Freiburg, Germany},
  abstract = {Artificial systems with a high degree of autonomy
                   require reliable semantic information about the
                   context they operate in. State interpretation,
                   however, is a difficult task. Interpretations may
                   depend on a history of states and there may be more
                   than one valid interpretation. We propose a model
                   for spatio-temporal situations using hidden Markov
                   models based on relational state descriptions,
                   which are extracted from the estimated state of an
                   underlying dynamic system. Our model covers
                   concurrent situations, scenarios with multiple
                   agents, and situations of varying durations. To
                   evaluate the practical usefulness of our model, we
                   apply it to the concrete task of online traffic
                   analysis.}
}
@inproceedings{pfaff07icra,
  author = {Pfaff, P. and Triebel, R.and Stachniss, C. and Lamon, P. and Burgard, W. and Siegwart, R.},
  title = {Towards Mapping of Citites},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2007,
  doi = {10.1109/ROBOT.2007.364220},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pfaff07icra.pdf},
  address = {Rome, Italy}
}
@inproceedings{pfaff07iros,
  author = {P. Pfaff and C. Plagemann and W. Burgard},
  title = {Improved Likelihood Models for Probabilistic
Localization based on Range Scans},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2007,
  doi = {10.1109/IROS.2007.4399250},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pfaff07iros.pdf},
  address = {San Diego, CA, USA},
  abstract = {}
}
@article{pfaff07ijrr,
  author = {Pfaff, P. and Triebel, R. and Burgard, W.},
  title = {An Efficient Extension to Elevation Maps for
Outdoor Terrain Mapping and Loop Closing},
  journal = {International Journal of Robotics Research},
  year = 2007,
  editor = {P. Corke, and S. Sukkarieh}
}
@inproceedings{plagemann07snowb,
  author = {Plagemann, C. and Kersting, K. and Pfaff, P.  and Burgard, W.},
  title = {Heteroscedastic Gaussian Process Regression for
Modeling Range Sensors in Mobile Robotics},
  booktitle = {Proc.~of the Learning Workshop (Snowbird)},
  year = 2007,
  month = mar,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann07snowb.pdf},
  address = {San Juan, Puerto Rico}
}
@inproceedings{rottmann07iros,
  author = {Rottmann, A. and Plagemann, C. and Hilgers, P. and Burgard, W.},
  title = {Autonomous Blimp Control using Model-free
Reinforcement Learning in a Continuous State and
Action Space},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  pages = {1895--1900},
  year = 2007,
  doi = {10.1109/IROS.2007.4399531},
  url = {http://ais.informatik.uni-freiburg.de/~rottmann/publication/rottmann07iros.pdf},
  address = {San Diego, CA, USA},
  abstract = {}
}
@inproceedings{plagemann07rss,
  author = {Plagemann, C. and Kersting, K. and Pfaff, P. and Burgard, W.},
  title = {Gaussian Beam Processes: A Nonparametric
Bayesian Measurement Model for Range Finders},
  booktitle = {Robotics: Science and Systems (RSS)},
  year = 2007,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann07rss.pdf},
  address = {Atlanta, Georgia, USA},
  abstract = {In probabilistic mobile robotics, the development
                   of measurement models plays a crucial role as it
                   directly influences the efficiency and the
                   robustness of the robot's performance in a great
                   variety of tasks including localization, tracking,
                   and map building. In this paper, we present a novel
                   probabilistic measurement model for range finders,
                   called Gaussian Beam Processes, which treats the
                   measurement modeling task as a nonparametric
                   Bayesian regression problem and solves it using
                   Gaussian processes. The major advantage of our
                   approach lies in the smoothness of the resulting
                   model which appropriately represents correlations
                   between adjacent beams using covariance functions.
                   Moreover, the Gaussian process treatment results in
                   a sound probabilistic measurement model with a pool
                   of well-established techniques for likelihood
                   estimation and range prediction for an arbitrary
                   number of beams. Experiments on real world and
                   synthetic data show that Gaussian Beam Processes
                   combine the advantages of two popular measurement
                   models.}
}
@inproceedings{lang07rss,
  author = {Lang, T. and Plagemann, C. and Burgard, W.},
  title = {Adaptive Non-Stationary Kernel Regression for
Terrain Modeling},
  booktitle = {Robotics: Science and Systems (RSS)},
  year = 2007,
  month = jun,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lang07rss.pdf},
  address = {Atlanta, Georgia, USA},
  abstract = {Three-dimensional digital terrain models are of
                   fundamental importance in many areas such as the
                   geo-sciences and outdoor robotics. Accurate
                   modeling requires the ability to deal with a
                   varying data density and to balance smoothing
                   against the preservation of discontinuities. The
                   latter is particularly important for robotics
                   applications, as discontinuities that arise, for
                   example, at steps, stairs, or building walls are
                   important features for path planning or terrain
                   segmentation tasks. In this paper, we present an
                   extension of the well- established Gaussian process
                   regression technique, that utilizes non-stationary
                   covariance functions to locally adapt to the
                   structure of the terrain data. In this way, we
                   achieve strong smoothing in flat areas and along
                   edges and at the same time preserve edges and
                   corners. The derived model yields predictive height
                   distributions for arbitrary locations of the
                   terrain and therefore allows us to fill gaps in
                   data and to perform conservative predictions in
                   occluded areas.}
}
@inproceedings{kersting07icml,
  author = {Kersting, K. and Plagemann, C. and Pfaff, P. and Burgard, W.},
  title = {Most Likely Heteroscedastic Gaussian Process
Regression},
  booktitle = {International Conference on Machine Learning
(ICML)},
  year = 2007,
  month = mar,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kersting07icml.pdf},
  address = {Corvallis, Oregon, USA},
  abstract = {This paper presents a novel Gaussian process (GP)
                   approach to regression with input-dependent noise
                   rates. We follow Goldberg et al.'s approach and
                   model the noise variance using a second GP in
                   addition to the GP governing the noise-free output
                   value. In contrast to Goldberg et al., however, we
                   do not use a Markov chain Monte Carlo method to
                   approximate the posterior noise variance but a most
                   likely noise approach. The resulting model is easy
                   to implement and can directly be used in
                   combination with various existing extensions of the
                   standard GPs such as sparse approximations.
                   Extensive experiments on both synthetic and real-
                   world data, including a challenging perception
                   problem in robotics, show the effectiveness of most
                   likely heteroscedastic GP regression.}
}
@article{kersting07ar,
  author = {Kersting, K. and Plagemann, C. and Cocora, A. and Burgard, W. and De Raedt, L.},
  title = {Learning to Transfer Optimal Navigation
Policies},
  journal = {Advanced Robotics. Special Issue on Imitative
Robots},
  volume = {21},
  number = {9},
  year = 2007,
  month = sep,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/kersting07ar.pdf},
  abstract = {Autonomous agents that act in the real world
                   utilizing sensory input greatly rely on the ability
                   to plan their actions and to transfer these skills
                   across tasks. The majority of path planning
                   approaches for mobile robots, however, solve the
                   current navigation problem from scratch given the
                   current and goal configuration of the robot.
                   Consequently, these approaches yield highly
                   efficient plans for the specific situation, but the
                   computed policies typically do not transfer to
                   other, similar tasks. In this paper, we propose to
                   apply techniques from statistical relational
                   learning to the path planning problem. More
                   precisely, we propose to learn relational decision
                   trees as abstract navigation strategies from
                   example paths. Relational abstraction has several
                   interesting and important properties. First, it
                   allows a mobile robot to imitate navigation
                   behavior shown by users or by optimal policies.
                   Second, it yields comprehensible models of
                   behavior. Finally, a navigation policy learned in
                   one environment naturally transfers to unknown
                   environments. In several experiments with real
                   robots and in simulated runs, we demonstrate that
                   our approach yields efficient navigation plans. We
                   show that our system is robust against observation
                   noise and can outperform hand-crafted policies.}
}
@inproceedings{plagemann07ijcai,
  author = {Plagemann, C. and Fox, D. and Burgard, W.},
  title = {Efficient Failure Detection on Mobile Robots
Using Particle Filters with Gaussian Process
Proposals},
  booktitle = {Proc.~of the Twentieth International Joint
Conference on Artificial Intelligence (IJCAI)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann07ijcai.pdf},
  address = {Hyderabad, India},
  abstract = {The ability to detect failures and to analyze
                   their causes is one of the preconditions of truly
                   autonomous mobile robots. Especially online failure
                   detection is a complex task, since the effects of
                   failures are typically difficult to model and often
                   resemble the noisy system behavior in a fault-free
                   operational mode. In this paper we present an
                   approach that applies Gaussian process
                   classification and regression techniques for
                   learning highly effective proposal distributions of
                   a particle filter that is applied to track the
                   state of the system.  As a result, the efficiency
                   and robustness of the state estimation process is
                   substantially improved. In practical experiments
                   carried out with a real robot we demonstrate that
                   our system is capable of detecting collisions with
                   unseen obstacles while at the same time estimating
                   the changing point of contact with the obstacle.}
}
@inproceedings{rottmann07ecmr,
  author = {Rottmann, A. and Sippel, M. and Zitterell, T. and Burgard, W. and Reindl, L. and Scholl, C.},
  title = {Towards an Experimental Autonomous Blimp
Platform},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/rottmann07ecmr.pdf},
  address = {Freiburg, Germany}
}
@inproceedings{steder07irosws,
  author = {Steder, B. and Rottmann, A. and Grisetti, G. and Stachniss, C. and Burgard, W.},
  title = {Autonomous Navigation for Small Flying
Vehicles},
  booktitle = {Workshop on Micro Aerial Vehicles at the
IEEE/RSJ Int.~Conf.~on Intelligent Robots and
Systems (IROS)},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder07irosws.pdf},
  address = {San Diego, CA, USA}
}
@incollection{burgard07starbook,
  author = {Burgard, W. and Stachniss, C. and Haehnel, D.},
  title = {Mobile Robot Map Learning from Range Data in
Dynamic Environments},
  booktitle = {Autonomous Navigation in Dynamic Environments},
  volume = {35},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/burgard07starbook.pdf},
  publisher = {Springer},
  editor = {Laugier, C. and Chatila, R.},
  series = {STAR Springer tracts in advanced robotics}
}
@inproceedings{stachniss07iros,
  author = {Stachniss, C. and Grisetti, G. and Burgard, W. and Roy, N.},
  title = {Evaluation of Gaussian Proposal Distributions
for Mapping with Rao-Blackwellized Particle
Filters},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2007,
  doi = {10.1109/IROS.2007.4399005},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss07iros.pdf},
  address = {San Diego, CA, USA}
}
@inproceedings{wurm07ecmr,
  author = {Wurm, K.M. and Stachniss, C. and Grisetti, G. and Burgard, W.},
  title = {Improved Simultaneous Localization and Mapping
using a Dual Representation of the Environment},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  year = 2007,
  month = sep,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm07ecmr.pdf},
  address = {Freiburg, Germany}
}
@incollection{martinez07starbook,
  author = {Mart\'{i}nez-Mozos, O. and Stachniss, C. and Rottmann, A. and Burgard, W.},
  title = {Using AdaBoost for Place Labelling and
Topological Map Building},
  booktitle = {Robotics Research},
  volume = {28},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/martinez07springer.pdf},
  publisher = {Springer},
  isbn = {978-3-540-48110-2},
  editor = {Thrun, S. and Brooks, R. and Durrant-Whyte, H.},
  series = {STAR Springer tracts in advanced robotics}
}
@article{grisetti07trans,
  author = {Grisetti, G. and Stachniss, C. and Burgard, W.},
  title = {Improved Techniques for Grid Mapping with Rao-
Blackwellized Particle Filters},
  journal = {IEEE Transactions on Robotics},
  volume = {23},
  number = {1},
  pages = {34--46},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti07tro.pdf}
}
@article{grisetti07jras,
  author = {Grisetti, G. and Tipaldi, G.D. and Stachniss, C. and Burgard, W. and Nardi, D.},
  title = {Fast and Accurate {SLAM} with Rao-Blackwellized
Particle Filters},
  journal = {Robotics and Autonomous Systems},
  volume = {55},
  number = {1},
  pages = {30--38},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/~tipaldi/papers/grisettiRAS07.pdf}
}
@mastersthesis{steder07da,
  author = {Steder, Bastian},
  title = {{T}echniken f{\"u}r bildbasiertes {SLAM} unter
{V}erwendung von {L}agesensoren},
  school = {Albert-Ludwigs-Universit{\"a}t},
  year = 2007,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/steder07da.pdf},
  address = {Freiburg}
}
@inproceedings{tipaldi07iros,
  author = {Gian Diego Tipaldi and Giorgio Grisetti and Wolfram Burgard},
  title = {Approximated Covariance Estimation in Graphical
Approaches to SLAM},
  booktitle = {Proceedings of the {IEEE/RSJ} International
Conference on Intelligent Robots and Systems
({IROS})},
  year = 2007,
  doi = {10.1109/IROS.2007.4399258},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/tipaldiIROS07.pdf},
  address = {San Diego, USA}
}
@mastersthesis{wurm07da,
  author = {Wurm, Kai M.},
  title = {Robustes {L}ernen von {U}mgebungskarten durch
{I}ntegration verschiedener {R}epr{\"a}sentationen},
  school = {Albert-Ludwigs-Universit{\"a}t},
  year = 2007,
  month = jul,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wurm07da.pdf},
  note = {In German},
  address = {Freiburg}
}
@inproceedings{mozos2006iros_w,
  author = {Oscar Martinez Mozos and Axel Rottmann and Rudolph Triebel and Patric Jensfelt and Wolfram Burgard},
  title = {Semantic Labeling of Places using Information
Extracted from Laser and Vision Sensor Data},
  booktitle = {Proceedings of the IEEE/RSJ IROS Workshop: From
sensors to human spatial concepts},
  pages = {391--402},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/~rottmann/publication/mozos2006iros_w.pdf},
  category = {workshop},
  address = {Beijing, China}
}
@inproceedings{mozos2006iros,
  author = {Oscar Martinez Mozos and Wolfram Burgard},
  title = {Supervised Learning of Topological Maps using
Semantic Information Extracted from Range Data.},
  booktitle = {IEEE/RSJ International Conference on
Intelligent Robots and Systems},
  year = 2006,
  doi = {10.1109/IROS.2006.282058},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mozos2006iros.pdf},
  category = {conference},
  address = {Beijing, China}
}
@inproceedings{gil2006iros,
  author = {Arturo Gil and Oscar Reinoso and Wolfram Burgard and Cyrill Stachniss and Oscar Martinez Mozos},
  title = {Improving Data Association in Rao-Blackwellized
visual {SLAM}},
  booktitle = {Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems},
  pages = {2076--2081},
  year = 2006,
  doi = {10.1109/IROS.2006.282483},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/gil2006iros.pdf},
  category = {conference},
  address = {Beijing, China}
}
@inproceedings{stachniss06icra,
  author = {Cyrill Stachniss and Oscar Martinez Mozos and Wolfram Burgard},
  title = {Speeding-Up Multi-Robot Exploration by
Considering Semantic Place Information},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics and Automation},
  pages = {1692--1697},
  year = 2006,
  doi = {10.1109/ROBOT.2006.1641950},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss06icra.pdf},
  link = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss2006icra.pdf},
  category = {conference},
  address = {Orlando, FL, USA}
}
@inproceedings{bennewitz06euros,
  author = {Bennewitz, M. and Stachniss, C. and Burgard, W. and Behnke, S.},
  title = {Metric Localization with Scale-Invariant Visual
Features using a Single Perspective Camera},
  booktitle = {European Robotics Symposium 2006},
  volume = {22},
  pages = {143--157},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz06euros.pdf},
  publisher = {Springer Verlag Berlin Heidelberg, Germany},
  isbn = {3-540-32688-X},
  editor = {H.I. Christiensen},
  series = {STAR Springer tracts in advanced robotics}
}
@proceedings{RSS06,
  title = {Proc.~of the Robotics - Science and Systems
(RSS)},
  year = 2006,
  editor = {Sukhatme, G. and Schaal, S. and Fox, D. and
                   Burgard, W.}
}
@inproceedings{mucientes2006iros,
  author = {Mucientes, M. and Burgard, W.},
  title = {Multi-Hypothesis Tracking of Clusters of
People},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2006,
  doi = {10.1109/IROS.2006.282614}
}
@mastersthesis{grzonka06thesis,
  author = {Grzonka, S.},
  title = {Untersuchungen zur Genauigkeit von SLAM-
Verfahren mit Partikel-Filtern},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/Grzonka_Diplomarbeit.pdf},
  note = {In German}
}
@inproceedings{lamon06irosws,
  author = {Lamon, P. and  Stachniss, C. and Triebel, R. and  Pfaff, P. andPlagemann, C. and Grisetti, G.  and Kolski, S.  and Burgard, W. and Siegwart, R.},
  title = {Mapping with an Autonomous Car},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/lamon06iros.pdf},
  address = {Beijing, China},
  abstract = {In this paper, we present an approach towards
                   mapping and safe navigation in real, large-scale
                   environments with an autonomous car. The goal is to
                   enable the car to autonomously navigate on roads
                   while avoiding obstacles and while simultaneously
                   learning an accurate three-dimensional model of the
                   environment. To achieve these goals, we apply
                   probabilistic state estimation techniques, network-
                   based pose optimization, and a sensor-based
                   traversability analysis approach. In order to
                   achieve fast map learning, our system compresses
                   the sensor data using multi-level surface maps. The
                   overall system runs on a modified Smart car
                   equipped with different types of sensors. We
                   present several results obtained from extensive
                   experiments which illustrate the capabilities of
                   our vehicle.}
}
@inproceedings{pfaff06euros,
  author = {Pfaff, P. and Burgard, W. and Fox, D.},
  title = {Robust Monte-Carlo Localization using Adaptive
Likelihood Models},
  booktitle = {European Robotics Symposium 2006},
  volume = {22},
  pages = {181--194},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pfaff06euros.pdf},
  publisher = {Springer-Verlag Berlin Heidelberg, Germany},
  isbn = {3-540-32688-X},
  editor = {H.I. Christiensen},
  series = {springerstaradvanced}
}
@inproceedings{triebel06iros,
  author = {R. Triebel and P. Pfaff and W. Burgard},
  title = {Multi Level Surface Maps for Outdoor Terrain
Mapping and Loop Closing},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2006,
  doi = {10.1109/IROS.2006.282632},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/triebel06iros.pdf}
}
@article{cocora06ki,
  author = {Cocora, A. and Kersting, K. and Plagemann, C. and Burgard, W. and De Raedt, L.},
  title = {Learning Relational Navigation Policies},
  journal = {KI - K{\"u}nstliche Intelligenz, Themenheft
Lernen und Selbstorganisation von Verhalten},
  volume = {3},
  pages = {12--18},
  year = 2006
}
@inproceedings{cocora06iros,
  author = {Cocora, A. and Kersting, K. and Plagemann, C. and Burgard, W. and De Raedt, L.},
  title = {Learning Relational Navigation Policies},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2006,
  doi = {10.1109/IROS.2006.282061},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/cocora06iros.pdf},
  address = {Beijing, China},
  abstract = {Navigation is one of the fundamental tasks for a
                   mobile robot. The majority of path planning
                   approaches has been designed to entirely solve the
                   given problem from scratch given the current and
                   goal configurations of the robot. Although these
                   approaches yield highly efficient plans, the
                   computed policies typically do not transfer to
                   other, similar tasks. We propose to learn
                   relational decision trees as abstract navigation
                   strategies from example paths. Relational
                   abstraction has several interesting and important
                   properties. First, it allows a mobile robot to
                   generalize navigation plans from specific examples
                   provided by users or exploration. Second, the
                   navigation policy learned in one environment can be
                   transferred to unknown environments. In several
                   experiments with real robots in a real environment
                   and in simulated runs, we demonstrate the
                   usefulness of our approach.}
}
@inproceedings{plagemann06euros,
  author = {Plagemann, C. and Stachniss, C. and Burgard, W.},
  title = {Efficient Failure Detection for Mobile Robots
using Mixed-Abstraction Particle Filters},
  booktitle = {European Robotics Symposium 2006},
  volume = {22},
  pages = {93--107},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann06euros.pdf},
  publisher = {Springer-Verlag Berlin Heidelberg, Germany},
  isbn = {3-540-32688-X},
  editor = {H.I. Christensen},
  series = {STAR Springer tracts in advanced robotics}
}
@inproceedings{gil2006icinco,
  author = {Arturo Gil, A. and Reinoso, O. and Fern\'{a}ndez, C. and Asunci\'{o}n
Vicente, M. and Rottmann, A. and Mart\'{i}nez Mozos, O.},
  title = {Simultaneous localization and mapping in
unmodified environments using stereo vision},
  booktitle = {Proc.~of the Int.~Conf.~on Informatics in
Control, Automation, and Robotics},
  pages = {302--309},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/gil06icinco.pdf}
}
@inproceedings{meier06sensor,
  author = {Meier, D. and Stachniss, C. and Burgard, W.},
  title = {Cooperative Exploration With Multiple Robots
Using Low Bandwidth Communication},
  booktitle = {Informationsfusion in der Mess- und
Sensortechnik},
  pages = {145--157},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meier06sensor.pdf},
  isbn = {3-86644-053-7},
  editor = {Beyerer, J.  and Puente Le\'{o}n, F. and Sommer,
                   K.-D.}
}
@inproceedings{gil06iros,
  author = {Gil, A. and Reinoso, O. and Mart\'{i}nez-Mozos, O. and Stachniss, C. and Burgard, W.},
  title = {Improving Data Association in Vision-based
{SLAM}},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  year = 2006,
  doi = {10.1109/IROS.2006.282483},
  address = {Beijing, China}
}
@article{sonntag06endod,
  author = {Sonntag, D. and Stachniss-Carp, S. and Stachniss, C. and Stachniss, V.},
  title = {Determination of Root Canal Curvatures before
and after Canal Preparation (Part II): A Method
based on Numeric Calculus},
  journal = {Aust Endod J},
  volume = {32},
  pages = {16--25},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sonntag06endod.pdf}
}
@phdthesis{stachniss06phd,
  author = {Stachniss, C.},
  title = {Exploration and Mapping with Mobile Robots},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2006,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss06phd.pdf}
}
@inproceedings{grisetti06icra,
  author = {Grisetti, G. and Tipaldi, G.D. and Stachniss, C. and Burgard, W. and Nardi, D.},
  title = {Speeding-Up Rao-Blackwellized {SLAM}},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  pages = {442--447},
  year = 2006,
  doi = {10.1109/ROBOT.2006.1641751},
  url = {http://ais.informatik.uni-freiburg.de/~tipaldi/papers/grisettiICRA06.pdf},
  address = {Orlando, FL, USA}
}
@inproceedings{stachniss05isrr,
  author = {Cyrill Stachniss and Oscar Martinez Mozos and Axel Rottmann and Wolfram Burgard},
  title = {Semantic Labeling of Places},
  booktitle = {International Symposium of Robotics Research},
  year = 2005,
  month = oct,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss05isrr.pdf},
  link = {http://ais.informatik.uni-freiburg.de/~rottmann/publication/stachniss05isrr.pdf},
  category = {workshop},
  address = {San Francisco, CA, USA}
}
@inproceedings{rottmann05aaai,
  author = {Axel Rottmann and Oscar Martinez Mozos and Cyrill Stachniss and Wolfram Burgard},
  title = {Semantic Place Classification of Indoor
Environments with Mobile Robots using Boosting.},
  booktitle = {Proceedings of the National Conference on
Artificial Intelligence},
  pages = {1306--1311},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/rottmann05aaai.pdf},
  link = {http://www2.informatik.uni-freiburg.de/~omartine/publications/rottmann2005aaai.html},
  video = {http://www2.informatik.uni-freiburg.de/~omartine/multimedia/fr079-6classes-hmm2.anim.avi},
  category = {conference},
  address = {Pittsburgh, PA, USA}
}
@inproceedings{martinez05icra,
  author = {Oscar Martinez Mozos and Cyrill Stachniss and Wolfram Burgard},
  title = {Supervised Learning of Places from Range Data
using {A}da{B}oost},
  booktitle = {Proceedings of the IEEE International
Conference on Robotics and Automation},
  pages = {1742--1747},
  year = 2005,
  doi = {10.1109/ROBOT.2005.1570363},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/martinez05icra.pdf},
  link = {http://ais.informatik.uni-freiburg.de/~omartine/publications/martinez2005icra.html},
  video = {http://ais.informatik.uni-freiburg.de/~omartine/multimedia/fr079-online-classification.anim.avi},
  category = {conference},
  address = {Barcelona, Spain},
  finalistbeststudentpaper = {http://ais.informatik.uni-
                   __________________freiburg.de/~omartine/images/icra
                   05-best-student- __________________paper-
                   finalist.jpg}
}
@incollection{bennewitz05geriatrie,
  author = {Bennewitz, M. and Burgard, W.},
  title = {Serviceroboter f{\"u}r den {P}flegebereich},
  booktitle = {Handbuch Geriatrie. Lehrbuch fr Praxis und
Klinik},
  year = 2005,
  note = {In German},
  publisher = {Deutsche Krankenhaus Verlagsgesellschaft mbH},
  editor = {A. M. Raem and H. Fenger and G. F. Kolb and T.
                   Nikolaus and L. Pientka and R. Rychlik and T.
                   V{\"o}mel},
  address = {D{\"u}sseldorf}
}
@article{bennewitz05ijrr,
  author = {Bennewitz, M. and Burgard, W. and Cielniak, G. and Thrun, S.},
  title = {Learning Motion Patterns of People for
Compliant Robot Motion},
  journal = {The International Journal of Robotics Research
(IJRR)},
  volume = {24},
  number = {1},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz05ijrr.pdf}
}
@book{Choset04,
  author = {Choset, H. and Lynch, K. and Hutchinson, S. and Kantor, G. and Burgard, W. and Kavraki, L. and Thrun, S.},
  title = {Principles of Robot Motion: Theory, Algorithms
and Implementation},
  year = 2005,
  publisher = {MIT Press}
}
@book{Thrun05,
  author = {Thrun, S. and Burgard, W. and Fox, D.},
  title = {Probabilistic Robotics},
  year = 2005,
  publisher = {MIT Press}
}
@article{Thrun05MineMapping,
  author = {S. Thrun and S. Thayer and W. Whittaker and C. Baker and W. Burgard and D. Ferguson and D. H\"{a}hnel and M. Montemerlo and A. Morris and Z. Omohundro and C. Reverte and W. Whittaker},
  title = {Autonomous Exploration and Mapping of Abandoned
Mines},
  journal = {IEEE Robotics \& Automation Magazine},
  volume = {11},
  number = {4},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ieeeram-mine-mapping.pdf}
}
@article{Wolf04ieeetro,
  author = {Wolf, J. and Burgard, W. and Burkhardt, H.},
  title = {Robust Vision-based Localization by Combining
an Image Retrieval System with {M}onte {C}arlo
Localization},
  journal = {IEEE Transactions on Robotics},
  volume = {21},
  number = {2},
  pages = {208--216},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wolf-ieeetro05.pdf}
}
@inproceedings{pfaff05fsr,
  author = {P. Pfaff and W. Burgard},
  title = {An Efficient Extension of Elevation Maps for
Outdoor Terrain Mapping},
  booktitle = {Proc. of the International Conference on Field
and Service Robotics (FSR)},
  pages = {165--176},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/pfaff_fsr05.pdf},
  address = {Port Douglas, QLD, Australia}
}
@inproceedings{plagemann05ams,
  author = {Plagemann, C. and Burgard, W.},
  title = {Sequential Parameter Estimation for Fault
Diagnosis in Mobile Robots Using Particle Filters.},
  booktitle = {Autonome Mobile Systeme 2005 (AMS)},
  pages = {197-202},
  year = 2005,
  publisher = {Springer}
}
@inproceedings{plagemann05dagm,
  author = {Plagemann, C. and M{\"u}ller, T. and Burgard, W.},
  title = {Vision-Based 3D Object Localization Using
Probabilistic Models of Appearance.},
  booktitle = {Pattern Recognition, 27th DAGM Symposium, Vienna, Austria},
  volume = {3663},
  pages = {184-191},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann05dagm.pdf},
  publisher = {Springer},
  editor = {Walter G. Kropatsch and Robert Sablatnig and Allan
                   Hanbury},
  series = {Lecture Notes in Computer Science}
}
@mastersthesis{rottmann05masterthesis,
  author = {Rottmann, A.},
  title = {Bild- und laserbasierte Klassifikation von
Umgebungen mit mobilen Robotern},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/rottmann05mt.pdf},
  note = {In German}
}
@article{stachniss05ar,
  author = {Stachniss, C. and H\"{a}hnel, D. and Burgard, W. and Grisetti, G.},
  title = {On Actively Closing Loops in Grid-based
{FastSLAM}},
  journal = {Advanced Robotics},
  volume = {19},
  number = {10},
  pages = {1059--1080},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss05ar.pdf}
}
@inproceedings{stachniss05robotics,
  author = {Stachniss, C. and Grisetti, G. and Burgard, W.},
  title = {Information Gain-based Exploration Using Rao-
Blackwellized Particle Filters},
  booktitle = {Proc.~of Robotics: Science and Systems (RSS)},
  pages = {65--72},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss05rss.pdf},
  address = {Cambridge, MA, USA}
}
@inproceedings{meier05ecmr,
  author = {Meier, D. and Stachniss, C. and Burgard, W.},
  title = {Coordinating Multiple Robots During Exploration
Under Communication With Limited Bandwidth},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  pages = {26--31},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/meier05ecmr.pdf},
  address = {Ancona, Italy}
}
@inproceedings{stachniss05aaai,
  author = {Stachniss, C. and Burgard, W.},
  title = {Mobile Robot Mapping and Localization in Non-Static Environments},
  booktitle = {Proc.~of the National Conf.~on Artificial Intelligence (AAAI)},
  pages = {1324--1329},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss05aaai.pdf},
  address = {Pittsburgh, PA, USA}
}
@article{trahaniasWebfair,
  author = {Trahanias, P. and Burgard, W. and Argyros, A. and H\"{a}hnel, D. and Baltzakis, H. and Pfaff, P. and Stachniss, C.},
  title = {{TOURBOT} and {WebFAIR}: Web-Operated Mobile
Robots for Tele-Presence in Populated Exhibitions},
  journal = {IEEE Robotics \& Automation Magazine},
  volume = {12},
  number = {2},
  pages = {77--89},
  year = 2005
}
@article{burgard05tro,
  author = {W. Burgard and M. Moors and C. Stachniss and F. Schneider},
  title = {Coordinated Multi-Robot Exploration},
  journal = {IEEE Transactions on Robotics},
  volume = {21},
  number = {3},
  pages = {376--386},
  year = 2005,
  doi = {10.1109/TRO.2004.839232},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/burgard05tro.pdf}
}
@inproceedings{burgard05snowbird,
  author = {Burgard, W. and Stachniss, C. and Grisetti, G.},
  title = {Information Gain-based Exploration Using Rao-
Blackwellized Particle Filters},
  booktitle = {Proc. of the Learning Workshop (Snowbird)},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/burgard05snowbird.pdf},
  address = {Snowbird, UT, USA}
}
@inproceedings{stachniss05icra,
  author = {Stachniss, C. and Grisetti, G. and Burgard, W.},
  title = {Recovering Particle Diversity in a Rao-Blackwellized Particle Filter for {SLAM} after Actively Closing Loops},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  pages = {667--672},
  year = 2005,
  doi = {10.1109/ROBOT.2005.1570192},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss05icra.pdf},
  address = {Barcelona, Spain}
}
@inproceedings{grisetti05icra,
  author = {Grisetti, G. and Stachniss, C. and Burgard, W.},
  title = {Improving Grid-based {SLAM} with Rao-
Blackwellized Particle Filters by Adaptive Proposals
and Selective Resampling},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  pages = {2443--2448},
  year = 2005,
  doi = {10.1109/ROBOT.2005.1570477},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/grisetti05icra.pdf},
  address = {Barcelona, Spain}
}
@inproceedings{triebel05aaai,
  author = {Triebel, R. and Burgard, W.},
  title = {Improving Simultaneous Localization and Mapping in 3D Using Global Constraints},
  booktitle = {Proc.~of the Conf.~of the  Association for the
Advancement of Artificial Intelligence (AAAI)},
  year = 2005,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/AAAI051TriebelR.pdf}
}
@inproceedings{triebel05icra,
  author = {Triebel, R. and Burgard, W. and Dellaert, F.},
  title = {Using Hierarchical EM to Extract Planes from 3D Range Scans},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2005,
  doi = {10.1109/ROBOT.2005.1570803},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/triebel05using.pdf}
}
@inproceedings{wolf05icra,
  author = {Wolf, D.F. and Sukhatme, G. and Fox, D. and Burgard, W.},
  title = {Autonomous Terrain Mapping and Classification Using Hidden Markov Models},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics and Automation (ICRA)},
  year = 2005,
  doi = {10.1109/ROBOT.2005.1570411},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wolf05icra.pdf}
}
@mastersthesis{martinez2004thesis,
  author = {Oscar Martinez Mozos},
  title = {Supervised Learning of Places from Range Data
using AdaBoost},
  school = {University of Freiburg},
  year = 2004,
  month = dec,
  url = {http://ais.informatik.uni-freiburg.de/~omartine/publications/martinez2004thesis.html},
  ps = {http://ais.informatik.uni-freiburg.de/~omartine/publications/martinez2004thesis.ps.gz},
  category = {thesis}
}
@phdthesis{bennewitz04phd,
  author = {Bennewitz, M.},
  title = {Mobile Robot Navigation in Dynamic
Environments},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thesis_bennewitz.pdf}
}
@inproceedings{bennewitz04soave,
  author = {Bennewitz, M. and Pastrana, J. and Burgard, W.},
  title = {Active Localization of Persons with a Mobile
Robot Based on Learned Motion Behaviors},
  booktitle = {Proc.~of the third Workshop on Selforganization
of Adaptive Behavior (SOAVE)},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz04soave.pdf}
}
@article{Thrun03IEEETRANS,
  author = {Thrun, S. and Martin, C. and Liu, Y. and H{\"a}hnel, D. and Emery Montemerlo, R. and Deepayan, C. and Burgard, W.},
  title = {A Real-Time Expectation Maximization Algorithm
for Acquiring Multi-Planar Maps of Indoor
Environments with Mobile Robots},
  journal = {IEEE Transactions on Robotics and Automation},
  volume = {20},
  number = {3},
  pages = {433-442},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun.3d-planar-mapping.pdf}
}
@inproceedings{haehnel04rfid,
  author = {H{\"a}hnel, D. and Burgard, W. and Fox, D. and Fishkin, K. and Philipose, M.},
  title = {Mapping and Localization with {RFID}
Technology},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel.icra04-rfid.pdf}
}
@inproceedings{sack04lines,
  author = {Sack, D. and Burgard, W.},
  title = {A Comparison of Methods for Line Extraction
from Range Data},
  booktitle = {Proc.~of the IVAC Symposium on Intelligent
Autonomous Vehicles (IAV)},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sack-iav04.pdf}
}
@inproceedings{veeck04poly,
  author = {Veeck, M. and Burgard, W.},
  title = {Learning Polyline Maps from Range Scan Data
Acquired with Mobile Robots},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/veeck04iros.pdf}
}
@mastersthesis{plagemann04mastersThesis,
  author = {Plagemann, C.},
  title = {{A}nsichtsbasierte {E}rkennung und
{L}okalisierung von {O}bjekten zur {I}nitialisierung
eines {V}erfolgungsprozesses},
  school = {University of Karlsruhe, Department of Computer
Science and Fraunhofer Institute IITB, Karlsruhe},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/plagemann04mastersThesis.pdf},
  note = {In German}
}
@inproceedings{stachniss04soave,
  author = {Stachniss, C. and Grisetti, G. and H\"{a}hnel, D. and Burgard, W.},
  title = {Improved Rao-Blackwellized Mapping by Adaptive
Sampling and Active Loop-Closure},
  booktitle = {Proc.~of the Workshop on Self-Organization of
AdaptiVE behavior (SOAVE)},
  pages = {1--15},
  year = 2004,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss04soave.pdf},
  address = {Ilmenau, Germany}
}
@inproceedings{stachniss04iros,
  author = {Stachniss, C. and H\"{a}hnel, D. and Burgard, W.},
  title = {Exploration with Active Loop-Closing for
{FastSLAM}},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  pages = {1505--1510},
  year = 2004,
  doi = {10.1109/IROS.2004.1389609},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss04iros.pdf},
  address = {Sendai, Japan}
}
@inproceedings{cielniak03ecmr,
  author = {Cielniak, G. and Bennewitz, M. and Burgard, W.},
  title = {Robust Localization of Persons Based on Learned
Motion Patterns},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/cielniak03ecmr.pdf}
}
@inproceedings{cielniak03ijcai,
  author = {Cielniak, G. and Bennewitz, M. and Burgard, W.},
  title = {Where is ...? {L}earning and Utilizing Motion
Patterns of Persons with Mobile Robots},
  booktitle = {Proc.~of the International Joint Conference on
Artificial Intelligence (IJCAI)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/cielniak03ijcai.pdf}
}
@inproceedings{bennewitz03icra,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Adapting Navigation Strategies Using Motions
Patterns of People},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2003,
  doi = {10.1109/ROBOT.2003.1241887},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz03icra.pdf}
}
@inproceedings{bennewitz03vspets,
  author = {Bennewitz, M. and Cielniak, G. and Burgard, W.},
  title = {Utilizing Learned Motion Patterns to Robustly
Track Persons},
  booktitle = {Proc.~of the Joint IEEE International Workshop
on Visual Surveillance and Performance Evaluation of
Tracking and Surveillance (VS-PETS)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz03vspets.pdf}
}
@inproceedings{Blanco02Image,
  author = {Blanco, J. and Burgard, W. and Sanz, R. and Fernandez, J.L.},
  title = {Fast Face Detection for Mobile Robots by
Integrating Laser Range Data with Vision},
  booktitle = {Proc.~of the International Conference on
Advanced Robotics (ICAR)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/icar2003blanco.pdf}
}
@article{Burgard03Tele,
  author = {Burgard, W. and Trahanias, P. and H{\"a}hnel, D. and Moors, M. and Schulz, D. and Baltzakis, H. and Argyros, A.},
  title = {Tele-presence in Populated Exhibitions through
Web-operated Mobile Robots},
  journal = {Journal of Autonomous Robots},
  volume = {15},
  pages = {299-316},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/telePresence_jar.pdf}
}
@proceedings{ECMR03,
  title = {Proc.~of the first {European} Conference on
Mobile Robots (ECMR)},
  year = 2003,
  editor = {Borkowski, A. and Burgard, W. and Zingaretti, P.}
}
@article{Haehnel033D,
  author = {H{\"a}hnel, D. and Burgard, W. and Thrun, S.},
  title = {Learning compact 3D models of indoor and
outdoor environments with a mobile robot},
  journal = {Robotics and Autonomous Systems},
  volume = {44},
  number = {1},
  pages = {15-27},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel.ras-03.pdf}
}
@inproceedings{Haehnel03Dynamic,
  author = {H{\"a}hnel, D. and Triebel, R. and Burgard, W. and Thrun, S.},
  title = {Map Building with Mobile Robots in Dynamic
Environments},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel_icra03.pdf}
}
@inproceedings{Haehnel03IJCAI,
  author = {H{\"a}hnel, D. and Thrun, S. and Burgard, W.},
  title = {An Extension of the {ICP} Algorithm for
Modeling Nonrigid Objects with Mobile Robots},
  booktitle = {Proc.~of the International Joint Conference on
Artificial Intelligence (IJCAI)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel-ijcai03.pdf}
}
@article{Haehnel03JRSJ,
  author = {H{\"a}hnel, D. and Schulz, D. and Burgard, W.},
  title = {Mobile Robot Mapping in Populated
Environments},
  journal = {Journal of the Robotics Society of Japan
(JRSJ)},
  volume = {7},
  number = {17},
  pages = {579-598},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel-populated.pdf}
}
@article{Schulz03IJRR,
  author = {Schulz, D. and Burgard, W. and Fox, D. Cremers, A.B.},
  title = {People Tracking with a Mobile Robot Using
Sample-based Joint Probabilistic Data Association
Filters},
  journal = {International Journal of Robotics Research
(IJRR)},
  volume = {22},
  number = {2},
  pages = {99-116},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/people-tracking-ijrr-03.ps.gz}
}
@inproceedings{Thrun03ICRA,
  author = {Thrun, S. and Ferguson, D. and H{\"a}hnel, D. and Montemerlo, M. and Triebel, R. and Burgard, W.},
  title = {A System for Volumetric Robotic Mapping of Abandoned Mines},
  booktitle = {Proc.~of the IEEE International Conference on Robotics \& Automation (ICRA)},
  year = 2003,
  doi = {10.1109/ROBOT.2003.1242260},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun.mine-mapping.pdf}
}
@inproceedings{Trahanias02Interactive,
  author = {Trahanias, P. and Burgard, W. and H{\"a}hnel, D. and Moors, M. and Schulz, D. and Baltzakis, H. and Argyros, A.},
  title = {Interactive Tele-presence in Populated
Exhibitions through {W}eb-operated Robots},
  booktitle = {Proc.~of the International Conference on
Advanced Robotics (ICAR)},
  year = 2003
}
@inproceedings{ferguson03nips,
  author = {Ferguson, D. and Morris, A. and H{\"a}hnel, D. and Baker, C. and Omohundro, Z. and Reverte, C. and Thayer, S. and Whittaker, W. and Burgard, W. and Thrun, S.},
  title = {An Autonomous Robotic System for Mapping
Abandoned Mines},
  booktitle = {Proc.~of the Conference on Neural Information
Processing (NIPS)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ferguson-nips03.pdf}
}
@inproceedings{haehnel03iros,
  author = {H{\"a}hnel, D. and Burgard, W. and Fox, D. and Thrun, S.},
  title = {A highly efficient {FastSLAM} algorithm for
generating cyclic maps of large-scale environments
from raw laser range measurements},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel-iros03.pdf}
}
@inproceedings{haehnel03isrr,
  author = {H{\"a}hnel, D. and Thrun, S. and Wegbreit, B. and Burgard, W.},
  title = {Towards Lazy Data Association in {SLAM}},
  booktitle = {Proc.~of the Int. Symposium of Robotics
Research (ISRR)},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel-isrr03.pdf}
}
@inproceedings{stachniss03dagstuhl,
  author = {Stachniss, C. and H\"{a}hnel, D. and Burgard, W.},
  title = {Grid-based {FastSLAM} and Exploration with
Active Loop Closing},
  booktitle = {Online Proc.~of the Dagstuhl Seminar on Robot
Navigation (Dagstuhl Seminar~03501)},
  year = 2003,
  address = {Dagstuhl, Germany}
}
@inproceedings{stachniss03iros,
  author = {Stachniss, C. and Burgard, W.},
  title = {Mapping and Exploration with Mobile Robots
using Coverage Maps},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  pages = {476--481},
  year = 2003,
  doi = {10.1109/IROS.2003.1250673},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss03iros.pdf},
  address = {Las Vegas, NV, USA}
}
@inproceedings{stachniss03ecmr,
  author = {Stachniss, C. and Burgard, W.},
  title = {Using Coverage Maps to Represent the
Environment of Mobile Robots},
  booktitle = {Proc.~of the European Conference on Mobile
Robots (ECMR)},
  pages = {59--64},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss03ecmr.pdf},
  address = {Radziejowice, Poland}
}
@inproceedings{stachniss03ijcai,
  author = {Stachniss, C. and Burgard, W.},
  title = {Exploring Unknown Environments with Mobile
Robots using Coverage Maps},
  booktitle = {Proc.~of the Int.~Conf.~on Artificial
Intelligence (IJCAI)},
  pages = {1127--1132},
  year = 2003,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss03ijcai.pdf},
  address = {Acapulco, Mexico}
}
@article{bennewitz02ras,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Finding and Optimizing Solvable Priority
Schemes for Decoupled Path Planning Techniques for
Teams of Mobile Robots},
  journal = {Robotics and Autonomous Systems},
  volume = {41},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz02ras.pdf}
}
@inproceedings{bennewitz02iros,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Using {EM} to Learn Motion Behaviors of Persons
with Mobile Robots},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2002,
  doi = {10.1109/IRDS.2002.1041440},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz02iros.pdf}
}
@inproceedings{bennewitz02icra,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Learning Motion Patterns of Persons for Mobile
Service Robots},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2002,
  doi = {10.1109/ROBOT.2002.1014268},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz02icra.pdf}
}
@inproceedings{bennewitz02robotik,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Learning Motion Patterns of Persons for Mobile
Service Robots},
  booktitle = {Proc. of the VDI-Conference Robotik 2002
(Robotik)},
  year = 2002
}
@incollection{Bur02Col,
  author = {Burgard, W. and Moors, M. and Schneider, F.},
  title = {Collaborative Exploration of Unknown
Environments with Teams of Mobile Robots},
  booktitle = {Advances in Plan-Based Control of Robotic
Agents},
  volume = {2466},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/burgard02dagstuhl.ps.gz},
  publisher = {Springer Verlag},
  editor = {Beetz, M. and Hertzberg, J. and Ghallab, M. and
                   Pollack, M.E.},
  series = {LNCS}
}
@inproceedings{Haehnel02Mapping,
  author = {H{\"a}hnel, D. and Schulz, D. and Burgard, W.},
  title = {Map Building with Mobile Robots in Populated
Environments},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel_iros02.pdf}
}
@inproceedings{Schulz02Statistical,
  author = {Schulz, D. and Moors, M. and Burgard, W. and Cremers, A.B.},
  title = {A Statistical Approach to Tracking Multiple
Moving People with a Mobile Robot and its
Application to Improved Tele-Presence},
  booktitle = {Proc.~of the VDI-Conference Robotik 2002
(Robotik)},
  year = 2002
}
@inproceedings{Wolf02Image,
  author = {Wolf, J. and Burgard, W. and Burkhardt, H.},
  title = {Using an Image Retrieval System for Vision-based Mobile Robot Localization},
  booktitle = {Proc. of the International Conference on Image and Video Retrieval (CIVR)},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wolf_civr02.pdf}
}
@inproceedings{Wolf02Robust,
  author = {Wolf, J. and Burgard, W. and Burkhardt, H.},
  title = {Robust Vision-based Localization for Mobile
Robots using an Image Retrieval System Based on
Invariant Features},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/wolf_icra02.pdf}
}
@inproceedings{burgard02Tourbot,
  author = {Burgard, W. and Trahanias, P. and H{\"a}hnel, D. and Moors, M. and Schulz, D. and Baltzakis, H. and Argyros A.},
  title = {TOURBOT and WebFAIR: Web-Operated Mobile Robots
for Tele-Presence in Populated Exhibitions},
  booktitle = {Proc.~of the IROS 02 Workshop on Robots in
Exhibition},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/burgard-iros02Workshop.pdf}
}
@inproceedings{haehnel02probabilistic,
  author = {H{\"a}hnel, D. and Burgard, W.},
  title = {Probabilistic Matching for 3D Scan
Registration},
  booktitle = {Proc.~of the VDI-Conference Robotik 2002
(Robotik)},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/haehnel-robotik2002.pdf}
}
@inproceedings{stachniss02iros,
  author = {Stachniss, C. and Burgard, W.},
  title = {An Integrated Approach to Goal-directed
Obstacle Avoidance under Dynamic Constraints for
Dynamic Environments},
  booktitle = {Proc.~of the IEEE/RSJ Int.~Conf.~on Intelligent
Robots and Systems (IROS)},
  pages = {508--513},
  year = 2002,
  doi = {10.1109/IRDS.2002.1041441},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss02iros.pdf},
  address = {Lausanne, Switzerland}
}
@mastersthesis{stachniss02diplom,
  author = {Stachniss, C.},
  title = {{Z}ielgerichtete {K}ollisionsvermeidung f{\"u}r
mobile {R}oboter in dynamischen {U}mgebungen},
  school = {University of Freiburg, Department of Computer
Science},
  year = 2002,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/stachniss02diplom.pdf},
  note = {In German}
}
@article{beetz01Iis,
  author = {Beetz, M. and Arbuckle, T. and Belker, T. and Bennewitz, M. and Burgard, W. and Cremers, A.~B. and Fox, D. and Grosskreutz, H. and H{\"a}hnel, D. and Schulz, D.},
  title = {Integrated Plan-based Control of Autonomous
Service Robots in Human Environments},
  journal = {IEEE Intelligent Systems},
  volume = {16},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/beetz01Iis.pdf}
}
@inproceedings{bennewitz01iros,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Exploiting Constraints During Prioritized Path
Planning for Teams of Mobile Robots},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 2001,
  doi = {10.1109/IROS.2001.973389},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz01iros.pdf}
}
@inproceedings{bennewitz01ki,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Constraint-based Optimization of Priority
Schemes for Decoupled Path Planning Techniques},
  booktitle = {Proc. of the 24th German / 9th Austrian
Conference on Artificial Intelligence},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz01ki.pdf},
  publisher = {Springer Verlag}
}
@inproceedings{bennewitz01icra,
  author = {Bennewitz, M. and Burgard, W. and Thrun, S.},
  title = {Optimizing Schedules for Prioritized Path
Planning of Multi-Robot Systems},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2001,
  doi = {10.1109/ROBOT.2001.932565},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz01icra.pdf}
}
@inproceedings{bennewitz01sirs,
  author = {Bennewitz, M. and Burgard, W.},
  title = {Finding Solvable Priority Schemes for Decoupled
Path Planning Techniques for Teams of Mobile
Robots},
  booktitle = {Proc.~of the 9th International Symposium on
Intelligent Robotic Systems (SIRS)},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz01sirs.pdf}
}
@inproceedings{Liu01Us,
  author = {Liu, Y. and Emery, R. and Chakrabarti, D. and Burgard, W. and Thrun, S.},
  title = {Using {EM} to Learn 3{D} Models of Indoor
Environments with Mobile Robots},
  booktitle = {Proc.~of the International Conference on
Machine Learning (ICML)},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun.3D-EM.ps.gz}
}
@article{Sch00Pro,
  author = {Schulz, D. and Burgard, W.},
  title = {Probabilistic State Estimation of Dynamic
Objects with a Moving Mobile Robot},
  journal = {Robotics and Autonomous Systems},
  volume = {34},
  number = {2-3},
  pages = {107-115},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/probabilistic-state-estimation-2001.pdf}
}
@incollection{Sch00Rob,
  author = {Burgard, W. and Schulz, D.},
  title = {Robust Visualization for Web-based Control of
Mobile Robots},
  booktitle = {Robots on the Web: Physical Interaction through
the Internet},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/MIT-Press.ps.gz},
  publisher = {MIT-Press},
  editor = {Goldberg, K. and Siegwart, R.}
}
@inproceedings{Schulz01Track,
  author = {Schulz, D. and Burgard, W. and Fox, D. and Cremers, A.B.},
  title = {Tracking Multiple Moving Targets with a Mobile
Robot using Particle Filters and Statistical Data
Association},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/multi-tracking-01.ps.gz}
}
@inproceedings{Schulz01Tracking,
  author = {Schulz, D. and Burgard, W. and Fox, D. and Cremers, A.B.},
  title = {Tracking Multiple Moving Objects with a Mobile
Robot},
  booktitle = {Proc.~of the IEEE Computer Society Conference
on Computer Vision and Pattern Recognition (CVPR)},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/schulz-tracking-cvpr2001.pdf}
}
@article{Thrun01Robust,
  author = {Thrun, S. and Fox, D. and Burgard, W. and Dellaert. F.},
  title = {Robust {M}onte-{C}arlo Localization for Mobile
Robots},
  journal = {Artificial Intelligence},
  volume = {128},
  number = {1-2},
  pages = {99-141},
  year = 2001,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/robustMonteCarlo.pdf}
}
@inproceedings{haehnel01models3d,
  author = {H{\"a}hnel, D. and Burgard, W. and Thrun, S.},
  title = {Learning Compact 3D Models of Indoor and
Outdoor Environments with a Mobile Robot},
  booktitle = {Proc.~of the fourth {European} workshop on
advanced mobile robots (EUROBOT)},
  year = 2001
}
@article{thrun00ijrr,
  author = {Thrun, S. and Beetz, M. and Bennewitz, M. and Burgard, W. and Cremers, A.~B. and Dellaert, D. and Fox, D. and H{\"a}hnel, D. and Rosenberg, C. and Schulte, J. and Schulz, D.},
  title = {Probabilistic Algorithms and the Interactive
Museum Tour-Guide Robot Minerva},
  journal = {International Journal of Robotics Research
(IJRR)},
  volume = {19},
  number = {11},
  pages = {972-999},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun00ijrr.pdf}
}
@inproceedings{bennewitz00ams,
  author = {Bennewitz, M. and Burgard, W.},
  title = {An Experimental Comparison of Path Planning
Techniques for Teams of Mobile Robots},
  booktitle = {Proc.~of the Fachgespr{\"a}che Autonome Mobile
Systeme (AMS)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz00ams.pdf}
}
@inproceedings{bennewitz00sirs,
  author = {Bennewitz, M. and Burgard, W.},
  title = {Coordinating the Motions of Multiple Mobile
Robots Using a Probabilistic Model},
  booktitle = {Proc.~of the 8th International Symposium on
Intelligent Robotic Systems (SIRS)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz00sirs.pdf}
}
@inproceedings{bennewitz00ecaiws,
  author = {Bennewitz, M. and Burgard, W.},
  title = {A Probabilistic Method for Planning Collision-
free Trajectories of Multiple Mobile Robots},
  booktitle = {Proc.~of the Workshop ``Service Robotics -
Applications and Safety Issues in an Emerging
Market'' at the 14th European Conference on
Artificial Intelligence (ECAI)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/bennewitz00ecaiws.pdf}
}
@inproceedings{Bur00Col,
  author = {Burgard, W. and Moors, M. and Fox, D. and Simmons, R. and Thrun, S.},
  title = {Collaborative Multi-Robot Exploration},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/exploration-ICRA2000.ps.gz}
}
@article{Bur99Exp,
  author = {Burgard, W. and Cremers, A.B. and Fox, D. and H{\"a}hnel, D. and Lakemeyer, G. and Schulz, D. and Steiner, W. and Thrun, S.},
  title = {Experiences with an Interactive Museum Tour-Guide Robot},
  journal = {Artificial Intelligence},
  volume = {114},
  number = {1-2},
  pages = {3-55},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/museum-ai-00.ps.gz}
}
@incollection{Fox00Eff,
  author = {Fox, D. and Burgard, W. and Kruppa, H. and Thrun, S.},
  title = {Efficient multi-robot localization based on
{M}onte {C}arlo approximation},
  booktitle = {Robotics Research: The Ninth International
Symposium},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/multi-mcl-isrr-99.ps.gz},
  publisher = {Springer-Verlag},
  editor = {Hollerbach, J. and Koditschek, D.},
  address = {London}
}
@incollection{Fox00Par,
  author = {Fox, D. and Thrun, S. and Dellaert, F. and Burgard, W.},
  title = {Particle filters for mobile robot
localization},
  booktitle = {Sequential {M}onte {C}arlo Methods in
Practice},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/particle-chapter-00.ps.gz},
  publisher = {Springer Verlag},
  editor = {Doucet, A. and de Freitas, N. and Gordon, N.},
  address = {New York}
}
@article{Fox00Pro,
  author = {Fox, D. and Burgard, W. and Kruppa, H. and Thrun, S.},
  title = {A Probabilistic Approach to Collaborative
Multi-Robot Localization},
  journal = {Autonomous Robots},
  volume = {8},
  number = {3},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/multi-mcl-journal-00.ps.gz}
}
@incollection{Knoll00Robotik,
  author = {Knoll, A. and Burgard, W. and Christaller, Th.},
  title = {Robotik},
  booktitle = {Handbuch der K{\"u}nstlichen Intelligenz},
  year = 2000,
  note = {In German},
  publisher = {Oldenbourg},
  editor = {G{\"o}rz, G. and Rollinger, C.-R. and
                   Schneeberger, J.}
}
@article{Sch00Sta,
  author = {Schulz, D. and Burgard, W. and Cremers, A.B.},
  title = {State Estimation Techniques for 3D-
Visualizations of Web-based Tele-operated Mobile
Robots},
  journal = {Proc.~of the German Conference on Artificial
Intelligence (KI), Germany},
  volume = {4},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/fb_burgard.pdf}
}
@article{Sch99Web,
  author = {Schulz, D. and Burgard, W. and Fox, D. and Thrun, S. and Cremers, A.B.},
  title = {Web Interfaces for Mobile Robots in Public
Places},
  journal = {IEEE Robotics \& Automation Magazine},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/web-ram-00.ps.gz}
}
@inproceedings{Sim00Coo,
  author = {Simmons, R. and Apfelbaum, D. and Burgard, W. and Fox, D. and Moors, M. and Thrun, S. and Younes, H.},
  title = {Coordination for Multi-Robot Exploration and
Mapping},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/exploration-AAAI2000.ps.gz}
}
@inproceedings{Thr00Mon,
  author = {Thrun, S. and Fox, D. and Burgard, W.},
  title = {Monte {C}arlo Localization with Mixture
Proposal Distributions},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun.mclmix.ps.gz}
}
@inproceedings{Thr00Rea,
  author = {Thrun, S. and Burgard, W. and Fox, D.},
  title = {A Real-Time Algorithm for Mobile Robot Mapping
With Applications to Multi-Robot and 3D Mapping},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 2000,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun.map3d.ps.gz}
}
@inproceedings{thrun99ki,
  author = {Thrun, S. and Bennewitz, M. and Burgard, W. and Cremers, A.B. and Dellaert, F. and Fox, D. and H{\"a}hnel, D. and Rosenberg, C. and Roy, N. and Schulte, J. and Schulz, D.},
  title = {MINERVA: A Tour-Guide Robot that learns},
  booktitle = {Proc.~of the the 23rd German Conference on
Artificial Intelligence (KI)},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun99ki.pdf},
  publisher = {Springer Verlag}
}
@inproceedings{thrun99icra,
  author = {Thrun, S. and Bennewitz, M. and Burgard, W. and Dellaert, F. and Fox, D. and H{\"a}hnel, D. and Rosenberg, C. and Roy, N. and Schulte, J. and Schulz, D.},
  title = {MINERVA: A Second-Generation Museum Tour-Guide
Robot},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 1999,
  doi = {10.1109/ROBOT.1999.770401},
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun99icra.pdf}
}
@inproceedings{thrun99fsr,
  author = {Thrun, S. and Bennewitz, M. and Burgard, W. and Cremers, A.B. and Dellaert, F. and Fox, D. and H{\"a}hnel, D. and Rosenberg, C. and Roy, N. and Schulte, J. and Schulz, D.},
  title = {Experiences with two Deployed Interactive Tour-
guide Robots},
  booktitle = {Proc.~of the International Conference on Field
and Service Robotics (FSR)},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/thrun99fsr.pdf}
}
@inproceedings{Bee97Act,
  author = {Beetz, M. and Burgard, W. and Cremers, A.B. and Fox, D.},
  title = {Active Localization for Service Robot
Applications},
  booktitle = {Proc.~of the 5th Symposium for Intelligent
Robotics Systems (SIRS'97), Stockholm, Sweden},
  year = 1997
}
@article{Bee98Int,
  author = {Beetz, M. and Burgard, W. and Fox, D. and Cremers, A.B.},
  title = {Integrating Active Localization into High-level Robot Control Systems},
  journal = {Robotics and Autonomous Systems},
  volume = {23},
  pages = {205-220},
  year = 1998,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ras-special-sirs-97.ps.gz}
}
@article{Buh95Mob,
  author = {Buhmann, J. and Burgard, W. and Cremers, A.B. and Fox, D. and Hofmann, T. and Schneider, F. and Strikos, J. and Thrun, S.},
  title = {The Mobile Robot \mbox{R}hino},
  journal = {AI Magazine},
  volume = {16},
  number = {2},
  pages = {31-38},
  year = 1995,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/rhino-ai-magazine.ps.gz}
}
@mastersthesis{Bur86PRO,
  author = {Burgard, W.},
  title = {{PROSPERT}: An Expert System for the Syntesis
of Chemical Processes},
  school = {University of Dortmund, Department of Computer
Science},
  year = 1987,
  note = {In German}
}
@phdthesis{Bur91Goa,
  author = {Burgard, W.},
  title = {Goal-directed Forward Chaining for Logic
Programs},
  school = {University of Bonn, Department of Computer
Science},
  year = 1991,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/dissertation_burgard.pdf}
}
@incollection{Bur95Goa,
  author = {Burgard, W},
  title = {Goal-directed forward chaining: A tuple-
oriented bottom-up approach},
  booktitle = {Logic Programming: Formal Methods and Practical
Applications},
  year = 1995,
  publisher = {Elsevier Science B.V.},
  editor = {Beierle, Ch. and Pl{\"u}mer, L.}
}
@inproceedings{Bur96Est,
  author = {Burgard, W. and Fox, D. and Hennig, D. and Schmidt, T.},
  title = {Estimating the Absolute Position of a Mobile
Robot Using Position Probability Grids},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 1996,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/localize-aaai-96.pdf}
}
@inproceedings{Bur96Kno,
  author = {Burgard, W. and Cremers, A.B. and Fox, D. and Heidelbach, M. and Kappel, A.M. and L{\"u}ttring\-haus-Kappel, S.},
  title = {Knowledge-enhanced {CO}-monitoring in Coal
Mines},
  booktitle = {Proc.~of the Ninth International Conference on
Industrial \& Engineering Applications of Artificial
Intelligence \& Expert Systems},
  year = 1996,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/iea-aie.ps.gz}
}
@inproceedings{Bur96Log,
  author = {Burgard, W. and Cremers, A.B. and Fox, D. and Heidelbach, M. and Kappel, A.M. and L{\"u}ttringhaus-Kappel, S.},
  title = {Logic Programming Tools Applied to Fire
Detection in Hard-coal Mines},
  booktitle = {Proc.~of the Joint International Conference and
Symposium on Logic Programming},
  year = 1996
}
@inproceedings{Bur96Pos,
  author = {Burgard, W. and Fox, D. and Hennig, D. and Schmidt, T.},
  title = {Position Tracking with Position Probability
Grids},
  booktitle = {Proc.~of the First Euromicro Workshop on
Advanced Mobile Robots},
  year = 1996,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/tracking.ps.gz},
  publisher = {IEEE Computer Society Press}
}
@inproceedings{Bur97Act,
  author = {Burgard, W. and Fox, D. and Thrun, S.},
  title = {Active Mobile Robot Localization},
  booktitle = {Proc.~of the International Joint Conference on
Artificial Intelligence (IJCAI)},
  year = 1997,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/active-ijcai-97.ps.gz}
}
@inproceedings{Bur97Fas,
  author = {Burgard, W. and Fox, D. and Hennig, D.},
  title = {Fast Grid-Based Position Tracking for Mobile
Robots},
  booktitle = {Proc.~of the German Conference on Artificial
Intelligence (KI), Germany},
  year = 1997,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/tracking-ki-97.ps.gz},
  publisher = {Springer Verlag}
}
@misc{Bur97Mus,
  author = {Burgard, W. and Cremers, A. B. and Fox, D. and H{\"a}hnel, D. and Lakemeyer, G. and Schulz, D. and Steiner, W. and Thrun, S.},
  title = {The {{\em RHINO}} museum tour-guide project},
  year = 1997,
  howpublished = {\tt http://www.iai.uni-
                   bonn.de/\symbol{126}rhino/tourguide}
}
@inproceedings{Bur97aAct,
  author = {Burgard, W. and Fox, D. and Thrun, S.},
  title = {Active Mobile Robot Localization by Entropy
Minimization},
  booktitle = {Proc.~of the Second Euromicro Workshop on
Advanced Mobile Robots},
  year = 1997,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/active-eurobot-97.ps.gz},
  publisher = {IEEE Computer Society Press}
}
@inproceedings{Bur98DML,
  author = {Burgard, W. and Derr, A. and Fox, D. and Cremers, A.B.},
  title = {Integrating global position estimation and
position tracking for mobile robots: the {D}ynamic
{M}arkov {L}ocalization approach},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 1998,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/dml-iros-98.ps.gz}
}
@inproceedings{Bur98Int,
  author = {Burgard, W. and Cremers, A.B. and Fox, D. and H{\"a}hnel, D. and Lakemeyer, G. and Schulz, D. and Steiner, W. and Thrun, S.},
  title = {The Interactive Museum Tour-Guide Robot},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 1998,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/museum-aaai98.ps.gz}
}
@inproceedings{Bur98Mus,
  author = {Burgard, W. and Cremers, A.B. and Fox, D. and H{\"a}hnel, D. and Lakemeyer, G. and Schulz, D. and Steiner, W. and Thrun, S.},
  title = {The Museum Tour-Guide Robot {RHINO}},
  booktitle = {Proc.~of Fachgespr{\"a}ch Autonome Mobile
Systeme {(AMS'98)}},
  year = 1998,
  address = {Karlsruhe, Germany}
}
@inproceedings{Bur98Rea,
  author = {Burgard, W. and Fox, D. and H{\"a}hnel, D. and Lakemeyer, G. and Schulz, D. and Steiner, W. and Thrun, S. and Cremers, A.B.},
  title = {Real Robots for the Real World --- The
\emph{RHINO} Museum Tour-guide Project},
  booktitle = {Proc.~of the AAAI 1998 Spring Symposium on
Integrating Robotics Research: Taking the Next
Leap},
  year = 1998
}
@incollection{Bur98Ver,
  author = {Burgard, W. and Cremers, A.B. and Fox, D. and H{\"a}hnel, D. and Kappel, A.M. and L{\"u}ttring\-haus{-}Kappel, S.},
  title = {{V}erbesserte {B}randfr{\"u}herkennung im
{S}teinkohlenbergbau durch {V}orhersage von
{CO-K}on\-zen\-tra\-tio\-nen},
  booktitle = {KI Themenheft Data Mining},
  volume = {1},
  year = 1998,
  note = {In German},
  publisher = {ScienTec Publishing GmbH}
}
@inproceedings{Bur99Son,
  author = {Burgard, W. and Fox, D. and Jans, H. and Matenar, C. and Thrun, S.},
  title = {Sonar-Based Mapping of Large-Scale Mobile Robot Environments Using {EM}},
  booktitle = {Proc.~of the International Conference on Machine Learning (ICML)},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/em-mapping-icml-99.ps.gz}
}
@inproceedings{Burgard90Efficiency,
  author = {Burgard, W.},
  title = {Efficiency Considerations on Goal-Directed
Forward Chaining for Logic Programs},
  booktitle = {Proceedings of the 4th workshop on Computer
Science Logic (CSL)},
  year = 1990
}
@inproceedings{Del99Mon,
  author = {Dellaert, F. and Fox, D. and Burgard, W. and Thrun, S.},
  title = {Monte {C}arlo {L}ocalization for Mobile Robots},
  booktitle = {Proc.~of the IEEE International Conference on Robotics \& Automation (ICRA)},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sampling-icra99.ps.gz}
}
@inproceedings{Del99Usi,
  author = {Dellaert, F. and Burgard, W. and Fox, D. and Thrun, S.},
  title = {Using the Condensation Algorithm for Robust, Vision-based Mobile Robot Localization},
  booktitle = {Proc.~of the IEEE Computer Society Conference
on Computer Vision and Pattern Recognition (CVPR)},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sampling-vision-cvpr-99.ps.gz}
}
@proceedings{EUROBOT99,
  title = {Proc.~of the third {European} Workshop on
Advanced Mobile Robots (EUROBOT)},
  year = 1999,
  editor = {Burgard, W. and Nehmzow, U. and Vestli, S. and
                   Schweizer, G.}
}
@inproceedings{Fox96Con,
  author = {Fox, D. and Burgard, W. and Thrun, S.},
  title = {Controlling Synchro-drive Robots with the
Dynamic Window Approach to Collision Avoidance},
  booktitle = {Proc.~of the IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS)},
  year = 1996,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/colli-iros.ps.gz}
}
@article{Fox97Dyn,
  author = {Fox, D. and Burgard, W. and Thrun, S.},
  title = {The Dynamic Window Approach to Collision
Avoidance},
  journal = {IEEE Robotics \& Automation Magazine},
  volume = {4},
  number = {1},
  year = 1997,
  month = mar,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/colli-ieee.ps.gz},
  abstract = {This approach, designed for mobile robots equipped
                   with synchro-drives, is derived directly from the
                   motion dynamics of the robot. In experiments, the
                   dynamic window approach safely controlled the
                   mobile robot RHINO at speeds of up to 95 cm/sec, in
                   populated and dynamic environments.}
}
@article{Fox98Act,
  author = {Fox, D. and Burgard, W. and Thrun, S.},
  title = {Active {M}arkov Localization for Mobile Robots},
  journal = {Robotics and Autonomous Systems},
  volume = {25},
  pages = {195-207},
  year = 1998,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/ras-active.ps.gz}
}
@inproceedings{Fox98Hyb,
  author = {Fox, D. and Burgard, W. and Thrun, S. and Cremers, A.B.},
  title = {A Hybrid Collision Avoidance Method For Mobile
Robots},
  booktitle = {Proc.~of the IEEE International Conference on
Robotics \& Automation (ICRA)},
  year = 1998,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/obstserver-icra98.ps.gz}
}
@inproceedings{Fox98Pos,
  author = {Fox, D. and Burgard, W. and Thrun, S. and Cremers, A.B.},
  title = {Position Estimation for Mobile Robots in
Dynamic Environments},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 1998,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/selection-aaai98.ps.gz}
}
@inproceedings{Fox99Col,
  author = {Fox, D. and Burgard, W. and Kruppa, H. and Thrun, S.},
  title = {Collaborative Multi-Robot Localization},
  booktitle = {Proc.~of the German Conference on Artificial
Intelligence (KI), Germany},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/multi-mcl-ki-99.ps.gz},
  publisher = {Springer Verlag}
}
@incollection{Fox99Mar,
  author = {Fox, D. and Burgard, W. and Thrun, S.},
  title = {Markov Localization for Reliable Robot
Navigation and People Detection},
  booktitle = {Modelling and Planning for Sensor-Based
Intelligent Robot Systems},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/localize-dagstuhl-99.ps.gz},
  publisher = {Springer Verlag},
  series = {LNCS}
}
@article{Fox99MarB,
  author = {Fox, D. and Burgard, W. and Thrun, S.},
  title = {Markov Localization for Mobile Robots in
Dynamic Environments},
  journal = {Journal of Artificial Intelligence Research
(JAIR)},
  volume = {11},
  pages = {391-427},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/localize-jair-99.ps.gz}
}
@inproceedings{Fox99Mon,
  author = {Fox, D. and Burgard, W. and Dellaert, F. and Thrun, S.},
  title = {Monte {C}arlo {L}ocalization: Efficient
Position Estimation for Mobile Robots},
  booktitle = {Proc.~of the National Conference on Artificial
Intelligence (AAAI)},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/sampling-aaai-99.ps.gz}
}
@techreport{Fox99Mul,
  author = {Fox, D. and Burgard, W. and Kruppa, H. and Thrun, S.},
  title = {A {M}onte {C}arlo Algorithm for Multi-Robot
Localization},
  number = {CMS-CS-99-120},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/multi-tr.ps.gz},
  institution = {Carnegie Mellon University}
}
@inproceedings{Fox99Pro,
  author = {Fox, D. and Burgard, W. and Thrun, S.},
  title = {Probabilistic Methods for Mobile Robot
Mapping},
  booktitle = {Proc.~of the IJCAI-99 Workshop on Adaptive
Spatial Representations of Dynamic Environments},
  year = 1999,
  url = {http://ais.informatik.uni-freiburg.de/publications/papers/mapping-ijcai-99.ps.gz},
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}
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}
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  year = 1998
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  address = {Cambridge, MA}
}
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