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2024

•   G. Fischer, M. Bergau, A. Gómez-Rosal, A. Wachaja, J. Gr}ater, M. Odenweller, U. Piechottka, F. Hoeflinger, N. Gosala, N. Wetzel, D. B}uscher, A. Valada, and W. Burgard.
Evaluation of a Smart Mobile Robotic System for Industrial Plant Inspection and Supervision. 2024.
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2023

•   I. Nematollahi, K. Yankov, W. Burgard, and T. Welschehold.
Robot Skill Generalization via Keypoint Integrated Soft Actor-Critic Gaussian Mixture Models.
In Proceedings of the International Symposium on Experimental Robotics (ISER), Chiang Mai, Thailand, 2023.
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•   A. Gómez-Rosal, M. Bergau, G. Fischer, A. Wachaja, J. Gr}ater, M. Odenweller, U. Piechottka, F. Hoeflinger, N. Gosala, N. Wetzel, D. B}uscher, A. Valada, and W. Burgard.
A Smart Robotic System for Industrial Plant Supervision.
arXiv preprint arXiv:2308.05612, 2023.
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•   M. R. Nallapareddy, K. Sirohi, P. L. Drews-Jr, W. Burgard, C.-H. Cheng, and A. Valada.
EvCenterNet: Uncertainty Estimation for Object Detection using Evidential Learning.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, USA, 2023.
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•   N. Vödisch, K. Petek, W. Burgard, and A. Valada.
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation.
arXiv preprint arXiv:2303.10147, 2023.
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•   K. Sirohi, S. Marvi, D. Büscher, and W. Burgard.
Uncertainty-aware panoptic segmentation.
IEEE Robotics and Automation Letters, 8(5):2629--2636, 2023.
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•   N. Gosala, K. Petek, P. L. Drews-Jr, W. Burgard, and A. Valada.
SkyEye: Self-Supervised Bird's-Eye-View Semantic Mapping Using Monocular Frontal View Images.
arXiv preprint arXiv:2302.04233, 2023.
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•   O. Mees, J. Borja-Diaz, and W. Burgard.
Grounding Language with Visual Affordances over Unstructured Data.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), London, UK, 2023.
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•   K. Sirohi, S. Marvi, D. Büscher, and W. Burgard.
Uncertainty-aware LiDAR Panoptic Segmentation.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), London, UK, 2023.
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•   C. Huang, O. Mees, A. Zeng, and W. Burgard.
Visual Language Maps for Robot Navigation.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), London, UK, 2023.
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2022

•   E. Rosete-Beas, O. Mees, G. Kalweit, J. Boedecker, and W. Burgard.
Latent Plans for Task Agnostic Offline Reinforcement Learning.
In Proceedings of the 6th Conference on Robot Learning (CoRL), Auckland, New Zealand, 2022.
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•   I. Nematollahi, E. Rosete-Beas, S. M. B. Azad, R. Rajan, F. Hutter, and W. Burgard.
T3VIP: Transformation-based 3D Video Prediction.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan, 2022.
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•   N. Dorka, T. Welschehold, and W. Burgard.
Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting.
In Proc. of the Workshop on Decision Awareness in Reinforcement Learning on International Conference on Machine Learning (ICML), 2022.
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•   O. Mees, L. Hermann, and W. Burgard.
What Matters in Language Conditioned Robotic Imitation Learning Over Unstructured Data.
IEEE Robotics and Automation Letters (RA-L), 7(4):11205--11212, 2022.
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•   O. Mees, L. Hermann, E. Rosete-Beas, and W. Burgard.
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks.
IEEE Robotics and Automation Letters (RA-L), 7(3):7327--7334, 2022.
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•   E. Chisari, T. Welschehold, J. Bödecker, W. Burgard, and A. Valada.
Correct Me if I am Wrong: Interactive Learning for Robotic Manipulation.
IEEE Robotics and Automation Letters, 2022.
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•   N. Vödisch, D. Cattaneo, W. Burgard, and A. Valada.
Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning.
arXiv preprint arXiv:2203.01578, 2022.
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•   O. Mees and W. Burgard.
Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks.
In Proc. of RSS Pioneers at Robotics: Science and Systems (RSS), New York, USA, 2022.
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•   I. Nematollahi, E. Rosete-Beas, A. Roefer, T. Welschehold, A. Valada, and W. Burgard.
Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, USA, 2022.
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•   K. Petek, K. Sirohi, D. Büscher, and W. Burgard.
Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimation.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, USA, 2022.
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•   J. Borja-Diaz, O. Mees, G. Kalweit, L. Hermann, J. Boedecker, and W. Burgard.
Affordance Learning from Play for Sample-Efficient Policy Learning.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, USA, 2022.
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•   S. Yan, T. Welschehold, D. Büscher, and W. Burgard.
Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning.
IEEE Robotics and Automation Letters, 7(1):191--198, 2022.
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2021

•   N. Dorka, J. Boedecker, and W. Burgard.
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning.
In Proc. of the Workshop on Deep Reinforcement Learning at the Conference on Neural Information Processing Systems (NeurIPS), December 2021.
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•   T. Caselitz.
Camera-based Mapping and Localization in Varying Lighting Conditions.
PhD thesis, University of Freiburg, Department of Computer Science, November 2021.
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•   M. Kollmitz.
Perception and Learning for Mobile Robots in Populated Environments.
PhD thesis, University of Freiburg, Department of Computer Science, May 2021.
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•   J. Zhang.
Learning Navigation Policies with Deep Reinforcement Learning.
PhD thesis, University of Freiburg, Department of Computer Science, April 2021.
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•   M. Krawez, T. Caselitz, J. Sundram, M. Van Loock, and W. Burgard.
Real-Time Outdoor Illumination Estimation for Camera Tracking in Indoor Environments.
IEEE Robotics and Automation Letters, 2021.
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•   O. Mees and W. Burgard.
Composing Pick-and-Place Tasks By Grounding Language.
In Proceedings of the International Symposium on Experimental Robotics (ISER), La Valletta, Malta, 2021.
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•   W. Winterhalter, F. Fleckenstein, C. Dornhege, and W. Burgard.
Localization for precision navigation in agricultural fields—Beyond crop row following.
Journal of Field Robotics, 38(3):429--451, 2021.
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2020

•   P. S. Schmitt.
Planning and Control for Industrial Manipulation.
PhD thesis, University of Freiburg, Department of Computer Science, December 2020.
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•   L. Luft.
Efficient Generalizations of Probabilistic Methods for Robot Localization and Mapping.
PhD thesis, University of Freiburg, Department of Computer Science, July 2020.
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•   A. Dewan.
Leveraging Motion and Semantic Cues for 3D Scene Understanding.
PhD thesis, University of Freiburg, Department of Computer Science, May 2020.
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•   F. Boniardi.
Methods for Mobile Robot Localization Using Architectural Floor Plans.
PhD thesis, University of Freiburg, Department of Computer Science, May 2020.
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•   A. Schaefer.
Highly Accurate Lidar-Based Mapping and Localization for Mobile Robots.
PhD thesis, University of Freiburg, Department of Computer Science, March 2020.
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•   A. Pretto, S. Aravecchia, W. Burgard, N. Chebrolu, C. Dornhege, T. Falck, F. Fleckenstein, A. Fontenla, M. Imperoli, R. Khanna, F. Liebisch, P. Lottes, A. Milioto, D. Nardi, S. Nardi, J. Pfeifer, M. Popović, C. Potena, C. Pradalier, E. Rothacker-Feder, I. Sa, A. Schaefer, R. Siegwart, C. Stachniss, A. Walter, W. Winterhalter, X. Wu, and J. Nieto.
Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution.
IEEE Robotics & Automation Magazine, 2020.
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•   M. Kollmitz, T. Koller, J. Boedecker, and W. Burgard.
Learning Human-Aware Robot Navigation from Physical Interaction via Inverse Reinforcement Learning.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 11025--11031, Las Vegas, USA, 2020.
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•   S. Yan, J. Zhang, D. Büscher, and W. Burgard.
Efficiency and Equity are Both Essential: A Generalized Traffic Signal Controller with Deep Reinforcement Learning.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5526--5533, Las Vegas, USA, 2020.
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•   J. Meyer, A. Eitel, T. Brox, and W. Burgard.
Improving Unimodal Object Recognition with Multimodal Contrastive Learning.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, 2020.
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•   J. Vertens, J. Zürn, and W. Burgard.
HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, 2020.
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•   N. Dorka, J. Meyer, and W. Burgard.
Modality-Buffet for Real-Time Object Detection.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, 2020.
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•   A. Dewan and W. Burgard.
DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.
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•   I. Nematollahi, O. Mees, L. Hermann, and W. Burgard.
Hindsight for Foresight: Unsupervised Structured Dynamics Models from Physical Interaction.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, 2020.
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•   J. Zürn, W. Burgard, and A. Valada.
Self-supervised visual terrain classification from unsupervised acoustic feature learning.
IEEE Transactions on Robotics, 2020.
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•   T. Caselitz, M. Krawez, J. Sundram, M. V. Loock, and W. Burgard.
Camera Tracking in Lighting Adaptable Maps of Indoor Environments.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.
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•   O. Mees, M. Merklinger, G. Kalweit, and W. Burgard.
Adversarial Skill Networks: Unsupervised Robot Skill Learning from Videos.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.
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•   O. Mees, A. Emek, J. Vertens, and W. Burgard.
Learning Object Placements For Relational Instructionsby Hallucinating Scene Representations.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.
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•   L. Hermann, M. Argus, A. Eitel, A. Amiranashvili, W. Burgard, and T. Brox.
Adaptive Curriculum Generation from Demonstrations for Sim-To-Real Visuomotor Control.
In Proceedings of the International Conference on Robotics and Automation (ICRA), Paris, France, 2020.
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•   M. Kollmitz, D. Büscher, and W. Burgard.
Predicting Obstacle Footprints from 2D Occupancy Maps by Learning from Physical Interactions.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020.
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•   H. Kolkhorst, J. Veit, W. Burgard, and M. Tangermann.
A Robust Screen-Free Brain-Computer Interface for Robotic Object Selection.
Frontiers in Robotics and AI, 7, 2020. Research Topic: Advances in the Integration of Brain-Machine Interfaces and Robotic Devices.
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2019

•   F. Boniardi, A. Valada, R. Mohan, T. Caselitz, and W. Burgard.
Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019.
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•   H. Kolkhorst, W. Burgard, and M. Tangermann.
Learning User Preferences for Trajectories from Brain Signals.
In Proceedings of the International Symposium on Robotics Research (ISRR), Hanoi, Vietnam, October 2019.
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•   M. Mittal, R. Mohan, W. Burgard, and A. Valada.
Vision-Based Autonomous UAV Navigation and Landing for Urban Search and Rescue.
In Proc. of the International Symposium on Robotics Research (ISRR), Hanoi, Vietnam, October 2019.
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•   L. Luft, F. Boniardi, A. Schaefer, D. Büscher, and W. Burgard.
On the Bayes Filter for Shared Autonomy.
IEEE Robotics and Automation Letters (RA-L), 4(4):3286--3293, October 2019.
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•   A. Schaefer, D. Büscher, J. Vertens, L. Luft, and W. Burgard.
Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans.
In European Conference on Mobile Robots (ECMR), pages 1--7, September 2019.
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•   A. Valada, R. Mohan, and W. Burgard.
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation.
International Journal of Computer Vision (IJCV), July 2019. Special Issue: Deep Learning for Robotic Vision.
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•   N. Radwan.
Leveraging Sparse and Dense Features for Reliable State Estimation in Urban Environments.
PhD thesis, University of Freiburg, Department of Computer Science, June 2019.
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•   J. Zhang, N. Wetzel, N. Dorka, J. Boedecker, and W. Burgard.
Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration.
In Proc. of the Workshop of Exploration in Reinforcement Learning at IEEE International Conference on Machine Learning (ICML), Long Beach, USA, June 2019.
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•   I. Nematollahi, D. Kuhner, T. Welschehold, and W. Burgard.
Augmenting Action Model Learning by Non-Geometric Features.
In 2019 IEEE International Conference on Robotics and Automation (ICRA). IEEE, May 2019.
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•   A. Schaefer, J. Vertens, D. Büscher, and W. Burgard.
A Maximum Likelihood Approach to Extract Finite Planes from 3-D Laser Scans.
In IEEE International Conference on Robotics and Automation (ICRA), pages 72--78, May 2019.
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•   A. Valada.
Discovering and Leveraging Deep Multimodal Structure for Reliable Robot Perception and Localization.
PhD thesis, University of Freiburg, Department of Computer Science, February 2019.
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•   F. Fleckenstein, W. Winterhalter, C. Dornhege, C. Pradalier, and W. Burgard.
Smooth Local Planning Incorporating Steering Constraints.
In 12th Conference on Field and Service Robotics (FSR), 2019.
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•   F. Wirnshofer, P. S. Schmitt, P. Meister, G. v. Wichert, and W. Burgard.
Robust, Compliant Assembly with Elastic Parts and Model Uncertainty.
In 2019 International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019.
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•   T. Welschehold, N. Abdo, C. Dornhege, and W. Burgard.
Combined Task and Action Learning from Human Demonstrations for Mobile Manipulation Applications.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hong Kong, China, 2019.
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•   P. S. Schmitt, F. Wirnshofer, K. M. Wurm, G. v. Wichert, and W. Burgard.
Planning Reactive Manipulation in Dynamic Environments.
In 2019 International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019.
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•   A. Eitel, N. Hauff, and W. Burgard.
Self-supervised Transfer Learning for Instance Segmentation through Physical Interaction.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 2019.
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•   P. Ruchti.
Robot Localization and Mapping in Dynamic Environments.
PhD thesis, University of Freiburg, Department of Computer Science, Autonomous Intelligent Systems Group, 2019.
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•   O. Mees, M. Tatarchenko, T. Brox, and W. Burgard.
Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macao, China, 2019.
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•   F. Wirnshofer, P. S. Schmitt, P. Meister, G. v. Wichert, and W. Burgard.
State Estimation in Contact-Rich Manipulation.
In 2019 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2019.
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•   H. Kolkhorst, J. Veit, W. Burgard, and M. Tangermann.
Heterogeneity of Event-Related Potentials in a Screen-Free Brain-Computer Interface.
In Proceedings of the 8th Graz Brain-Computer Interface Conference 2019, Graz, Austria, 2019.
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•   H. Kolkhorst, S. Kärkkäinen, A. F. Raheim, W. Burgard, and M. Tangermann.
Influence of User Tasks on EEG-Based Classification Performance in a Hazard Detection Paradigm.
In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019.
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•   N. Radwan and W. Burgard.
Multitask Learning for Reliable State Estimation.
In Proc. of RSS Pioneers at Robotics: Science and Systems (RSS), Freiburg, Germany, 2019.
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•   J. Zhang, L. Tai, Y. Peng, Y. Xiong, M. Liu, J. Boedecker, and W. Burgard.
VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control.
IEEE Robotics and Automation Letters (RA-L), 4(2):1148--1155, 2019.
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•   P. S. Schmitt, F. Wirnshofer, K. M. Wurm, G. V. Wichert, and W. Burgard.
Modeling and Planning Manipulation in Dynamic Environments.
In 2019 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2019.
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•   M. Kollmitz, A. Eitel, A. Vasquez, and W. Burgard.
Deep 3D perception of people and their mobility aids.
Robotics and Autonomous Systems, 114:29--40, 2019.
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•   F. Boniardi, T. Caselitz, R. Kümmerle, and W. Burgard.
A Pose Graph-based Localization System for Long-term Navigation in CAD Floor Plans.
Robotics and Autonomous Systems, 112:84 -- 97, 2019.
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2018

•   H. Kolkhorst, M. Tangermann, and W. Burgard.
Guess What I Attend: Interface-Free Object Selection Using Brain Signals.
In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 7111--7116, Madrid, Spain, October 2018.
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•   A. Schaefer, D. Büscher, L. Luft, and W. Burgard.
A Maximum Likelihood Approach to Extract Polylines from 2-D Laser Range Scans.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4766--4773, October 2018.
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•   S. Glaser, A. Schaefer, and W. Burgard.
Mapping and Localization using Multispectral Imaging of the Soil.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Unconventional Sensing and Processing for Robotic Visual Perception Workshop, October 2018.
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•   P. Ruchti and W. Burgard.
Mapping with Dynamic-Object Probabilities Calculated from Single 3D Range Scans.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, May 2018.
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•   L. Luft, A. Schaefer, T. Schubert, and W. Burgard.
Detecting Changes in the Environment Based on Full Posterior Distributions Over Real-Valued Grid Maps.
IEEE Robotics and Automation Letters (RA-L), 3(2):1299--1305, April 2018.
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•   A. Schaefer, L. Luft, and W. Burgard.
DCT Maps: compact Differentiable Lidar Maps Based on the Cosine Transform.
IEEE Robotics and Automation Letters (RA-L), 3(2):1002--1009, April 2018.
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•   F. Wirnshofer, P. S. Schmitt, W. Feiten, G. v. Wichert, and W. Burgard.
Robust, Compliant Assembly via Optimal Belief Space Planning.
In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages 1--5. IEEE, 2018.
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•   L. Luft, T. Schubert, S. I. Roumeliotis, and W. Burgard.
Recursive decentralized localization for multi-robot systems with asynchronous pairwise communication.
The International Journal of Robotics Research, 37(10):1152--1167, 2018.
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•   T. Welschehold, C. Dornhege, F. Paus, T. Asfour, and W. Burgard.
Coupling Mobile Base and End-Effector Motion in Task Space.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
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•   M. Krawez, T. Caselitz, D. Büscher, M. V. Loock, and W. Burgard.
Building Dense Reflectance Maps of Indoor Environments using an RGB-D Camera.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
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•   A. Dewan, T. Caselitz, and W. Burgard.
Learning a Local Feature Descriptor for 3D LiDAR Scans.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
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•   M. Mittal, A. Valada, and W. Burgard.
Vision-based Autonomous Landing in Catastrophe-Struck Environments.
In Proc. of the Workshop on Vision-based Drones: What's Next? at IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
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•   N. Radwan, A. Valada, and W. Burgard.
VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry.
IEEE Robotics and Automation Letters (RA-L), 3(4):4407--4414, 2018.
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•   D. Kuhner, J. Aldinger, F. Burget, M. Göbelbecker, W. Burgard, and B. Nebel.
Closed-Loop Robot Task Planning Based on Referring Expressions.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
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•   N. Radwan and W. Burgard.
Effective Interaction-aware Trajectory Prediction using Temporal Convolutional Neural Networks.
In Proc. of the Workshop on Crowd Navigation: Current Challenges and New Paradigms for Safe Robot Navigation in Dense Crowds at IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
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•   W. Winterhalter, F. Fleckenstein, C. Dornhege, and W. Burgard.
Crop Row Detection on Tiny Plants With the Pattern Hough Transform.
IEEE Robotics and Automation Letters (RA-L), 3(4):3394--3401, 2018.
bib | DOI | .pdf ]
•   C. Menéndez-Romero, M. Sezer, F. Winkler, C. Dornhege, and W. Burgard.
Courtesy Behavior for Highly Automated Vehicles on Highway Interchanges.
In IEEE Intelligent Vehicles Symposium (IV), pages 943--948, 2018.
bib | DOI | .pdf ]
•   A. Valada, N. Radwan, and W. Burgard.
Incorporating Semantic and Geometric Priors in Deep Pose Regression.
In Proc. of the Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models at Robotics: Science and Systems (RSS), Pittsburgh, USA, 2018.
bib | .pdf ]
•   A. Valada and W. Burgard.
Learning Reliable and Scalable Representations Using Multimodal Multitask Deep Learning.
In Proc. of RSS Pioneers at Robotics: Science and Systems (RSS), Pittsburgh, USA, 2018.
bib | .pdf ]
•   C. Do and W. Burgard.
Accurate Pouring with an Autonomous Robot Using an RGB-D Camera.
In The 15th International Conference on Intelligent Autonomous Systems (IAS), Baden Baden, Germany, 2018.
bib | .pdf ]
•   C. Zimmermann, T. Welschehold, C. Dornhege, T. Brox, and W. Burgard.
3D Human Pose Estimation in RGBD Images for Robotic Task Learning.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, 2018.
bib | .pdf ]
•   M. Kollmitz, D. Büscher, T. Schubert, and W. Burgard.
Whole-Body Sensory Concept for Compliant Mobile Robots.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, 2018.
bib | .pdf ]
•   O. Zhelo, J. Zhang, L. Tai, M. Liu, and W. Burgard.
Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning.
In Proc. of the Workshop in Machine Learning in the Planning and Control of Robot Motion at IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, 2018.
bib | .pdf ]
•   L. Tai, J. Zhang, M. Liu, and W. Burgard.
Socially Compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, 2018.
bib | .pdf ]
•   P. Jund, A. Eitel, N. Abdo, and W. Burgard.
Optimization Beyond the Convolution: Generalizing Spatial Relations with End-to-End Metric Learning.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, 2018.
bib | .pdf ]
•   A. Valada, N. Radwan, and W. Burgard.
Deep Auxiliary Learning for Visual Localization and Odometry.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Brisbane, Australia, 2018.
bib | .pdf ]

2017

•   F. Kraemer, A. Schaefer, A. Eitel, J. Vertens, and W. Burgard.
From Plants to Landmarks: time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Agri-Food Robotics Workshop, September 2017.
bib | .pdf ]
•   L. Luft*, A. Schaefer*, T. Schubert, and W. Burgard.
Closed-Form Full Map Posteriors for Robot Localization with Lidar Sensors.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 6678--6684, September 2017.
bib | DOI | .pdf ]
•   A. Schaefer*, L. Luft*, and W. Burgard.
An Analytical Lidar Sensor Model Based on Ray Path Information.
IEEE Robotics and Automation Letters (RA-L), 2(3):1405--1412, July 2017.
bib | DOI | .pdf ]
•   P. S. Schmitt, W. Neubauer, W. Feiten, K. M. Wurm, G. V. Wichert, and W. Burgard.
Optimal, sampling-based manipulation planning.
In 2017 IEEE International Conference on Robotics and Automation (ICRA), pages 3426--3432. IEEE, 2017.
bib | DOI | .pdf ]
•   C. Menéndez-Romero, F. Winkler, C. Dornhege, and W. Burgard.
Maneuver planning for highly automated vehicles.
In IEEE Intelligent Vehicles Symposium (IV), pages 1458--1464, 2017.
bib | DOI | .pdf ]
•   G. Oliveira, N. Radwan, W. Burgard, and T. Brox.
Topometric Localization with Deep Learning.
In Proc. of the International Symposium on Robotics Research (ISRR), Puerto Varas, Chile, 2017.
bib | .pdf ]
•   A. Eitel, N. Hauff, and W. Burgard.
Learning to Singulate Objects using a Push Proposal Network.
In Proc. of the International Symposium on Robotics Research (ISRR), Puerto Varas, Chile, 2017.
bib | .pdf ]
•   W. Burgard, A. Valada, N. Radwan, T. Naseer, J. Zhang, J. Vertens, O. Mees, A. Eitel, and G. Oliveira.
Perspectives on Deep Multimodel Robot Learning.
In Proc. of the International Symposium on Robotics Research (ISRR), Puerto Varas, Chile, 2017.
bib | .pdf ]
•   A. Kuhner, T. Schubert, M. Cenciarini, I. K. Wiesmeier, V. A. Coenen, W. Burgard, C. Weiller, and C. Maurer.
Correlations between Motor Symptoms across Different Motor Tasks, Quantified via Random Forest Feature Classification in Parkinson’s Disease.
Frontiers in Neurology, 8:607, 2017.
bib | DOI | http ]
•   F. Burget, L. D. J. Fiederer, D. Kuhner, M. Völker, J. Aldinger, R. T. Schirrmeister, C. Do, J. Boedecker, B. Nebel, T. Ball, and W. Burgard.
Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills.
In Proc. of the IEEE European Conference on Mobile Robotics (ECMR), Paris, France, 2017.
bib | .pdf ]
•   A. Vasquez, M. Kollmitz, A. Eitel, and W. Burgard.
Deep Detection of People and their Mobility Aids for a Hospital Robot.
In Proc. of the IEEE European Conference on Mobile Robotics (ECMR), 2017.
bib | .pdf ]
•   J. Zhang, J. T. Springenberg, J. Boedecker, and W. Burgard.
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments.
In Proc.  of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   T. Naseer and W. Burgard.
Deep Regression for Monocular Camera-based 6-DoF Global Localization in Outdoor Environments.
In Proc.  of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   F. Boniardi, T. Caselitz, R. Kümmerle, and W. Burgard.
Robust LiDAR-based Localization in Architectural Floor Plans.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.
bib | DOI | .pdf ]
•   T. Welschehold, C. Dornhege, and W. Burgard.
Learning Mobile Manipulation Actions from Human Demonstrations.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.
bib | .pdf ]
•   A. Kuhner, T. Schubert, C. Maurer, and W. Burgard.
An Online System for Tracking the Performance of Parkinson's Patients.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   A. Schiotka, B. Suger, and W. Burgard.
Robot Localization with Sparse Scan-based Maps.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   A. Valada and W. Burgard.
Deep Spatiotemporal Models for Robust Proprioceptive Terrain Classification.
The International Journal of Robotics Research (IJRR), 36(13--14):1521--1539, 2017.
bib | DOI | .pdf ]
•   H. Kolkhorst, W. Burgard, and M. Tangermann.
Decoding Hazardous Events in Driving Videos.
In Proceedings of the 7th Graz Brain-Computer Interface Conference 2017, pages 242--247, Graz, Austria, 2017.
bib | DOI | .pdf ]
•   N. Chebrolu, P. Lottes, A. Schaefer, W. Winterhalter, W. Burgard, and C. Stachniss.
Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields.
The International Journal of Robotics Research (IJRR), 36(10):1045--1052, 2017.
bib | DOI | arXiv | http ]
•   N. Radwan, W. Winterhalter, C. Dornhege, and W. Burgard.
Why Did the Robot Cross the Road? - Learning from Multi-Modal Sensor Data for Autonomous Road Crossing.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   J. Vertens, A. Valada, and W. Burgard.
SMSnet: Semantic Motion Segmentation using Deep Convolutional Neural Networks.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   A. Dewan, G. L. Oliveira, and W. Burgard.
Deep Semantic Classification for 3D LiDAR Data.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017.
bib | .pdf ]
•   B. Suger and W. Burgard.
Global Outer-Urban Navigation with OpenStreetMap.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Singapore, Singapore, 2017.
bib | .pdf ]
•   T. Naseer, B. Suger, M. Ruhnke, and W. Burgard.
Vision-based Markov Localization for Long-term Autonomy.
Robotics and Autonomous Systems (RAS), 2017.
bib | http ]
•   T. Naseer, G. Oliveira, T. Brox, and W. Burgard.
Semantics-aware Visual Localization under Challenging Perceptual Conditions.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Singapore, 2017.
bib | .pdf ]
•   F. Fleckenstein, C. Dornhege, and W. Burgard.
Efficient Path Planning for Mobile Robots with Adjustable Wheel Positions.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Singapore, 2017.
bib | .pdf ]
•   O. Mees, N. Abdo, M. Mazuran, and W. Burgard.
Metric Learning for Generalizing Spatial Relations to New Objects.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.
bib | .pdf ]
•   A. Valada, J. Vertens, A. Dhall, and W. Burgard.
AdapNet: Adaptive Semantic Segmentation in Adverse Environmental Conditions.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Singapore, 2017.
bib | .pdf ]
•   H. Kolkhorst, M. Tangermann, and W. Burgard.
Decoding Perceived Hazardousness from User's Brain States to Shape Human-Robot Interaction.
In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, pages 349--350, Vienna, Austria, 2017.
bib | DOI | .pdf ]
•   D. Speck, C. Dornhege, and W. Burgard.
Shakey 2016 - How Much Does it Take to Redo Shakey the Robot?
IEEE Robotics and Automation Letters (RA-L), 2(2):1203--1209, 2017.
bib | DOI | .pdf ]

2016

•   P. Jund, N. Abdo, A. Eitel, and W. Burgard.
The Freiburg Groceries Dataset. abs/1611.05799, November 2016.
bib | .pdf ]
•   A. Valada, A. Dhall, and W. Burgard.
Convoluted Mixture of Deep Experts for Robust Semantic Segmentation.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop, State Estimation and Terrain Perception for All Terrain Mobile Robots, Daejeon, Korea, October 2016.
bib | .pdf ]
•   A. Valada, G. Oliveira, T. Brox, and W. Burgard.
Deep Multispectral Semantic Scene Understanding of Forested Environments using Multimodal Fusion.
In The 2016 International Symposium on Experimental Robotics (ISER 2016), Tokyo, Japan, October 2016.
bib | .pdf ]
•   A. Valada, G. Oliveira, T. Brox, and W. Burgard.
Towards Robust Semantic Segmentation using Deep Fusion.
In Robotics: Science and Systems (RSS 2016) Workshop, Are the Sceptics Right? Limits and Potentials of Deep Learning in Robotics, Ann Arbor, USA, June 2016.
bib | .pdf ]
•   L. Luft, T. Schubert, S. I. Roumeliotis, and W. Burgard.
Recursive Decentralized Collaborative Localization for Sparsely Communicating Robots.
In Proceedings of Robotics: Science and Systems, AnnArbor, Michigan, June 2016.
bib | DOI | .pdf ]
•   P. Schopp, H. Graf, W. Burgard, and Y. Manoli.
Self-Calibration of Accelerometer Arrays.
IEEE Transactions on Instrumentation and Measurement, 65(8):1913--1925, 2016.
bib | DOI | .pdf ]
•   N. Abdo, C. Stachniss, L. Spinello, and W. Burgard.
Organizing objects by predicting user preferences through collaborative filtering.
The International Journal of Robotics Research, 2016.
bib | DOI | .pdf ]
•   T. Welschehold, C. Dornhege, and W. Burgard.
Learning Manipulation Actions from Human Demonstrations.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3772--3777, Daejeon, Korea, 2016.
bib | DOI | .pdf ]
•   F. Burget, M. Bennewitz, and W. Burgard.
BI2RRT*: An efficient sampling-based path planning framework for task-constrained mobile manipulation.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3714--3721, Daejeon, Korea, 2016.
bib | DOI | .pdf ]
•   C. Gordillo, B. Frank, I. Ulbert, O. Paul, P. Ruther, and W. Burgard.
Automatic channel selection in neural microprobes: A combinatorial multi-armed bandit approach.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1844--1850, Daejeon, Korea, 2016.
bib | DOI | .pdf ]
•   C. Do, T. Schubert, and W. Burgard.
A Probabilistic Approach to Liquid Level Detection in Cups Using an RGB-D Camera.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
bib | .pdf ]
•   A. Wachaja, P. Agarwal, M. Zink, M. R. Adame, K. Möller, and W. Burgard.
Navigating blind people with walking impairments using a smart walker.
Autonomous Robots, pages 1--19, 2016.
bib | DOI | .pdf ]
•   A. Kuhner, T. Schubert, M. Cenciarini, C. Maurer, and W. Burgard.
A Probabilistic Approach Based on Random Forests to Estimating Similarity of Human Motion in the Context of Parkinson's Disease.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
bib | .pdf ]
•   B. Suger, B. Steder, and W. Burgard.
Terrain-Adaptive Obstacle Detection.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
bib | .pdf ]
•   T. Caselitz, B. Steder, M. Ruhnke, and W. Burgard.
Monocular Camera Localization in 3D LiDAR Maps.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
bib | .pdf ]
•   O. Mees, A. Eitel, and W. Burgard.
Choosing Smartly: Adaptive Multimodal Fusion for Object Detection in Changing Environments.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
bib | .pdf ]
•   A. Dewan, T. Caselitz, G. D. Tipaldi, and W. Burgard.
Rigid Scene Flow for 3D LiDAR Scans.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
bib | .pdf ]
•   G. Oliveira, W. Burgard, and T. Brox.
Efficient Deep Models for Monocular Road Segmentation.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), Daejeon, Korea, 2016.
bib | .pdf ]
•   T. Schubert, K. Eggensperger, A. Gkogkidis, F. Hutter, T. Ball, and W. Burgard.
Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Stockholm, Sweden, 2016.
bib | .pdf ]
•   G. Oliveira, A. Valada, C. Bollen, W. Burgard, and T. Brox.
Deep Learning for Human Part Discovery in Images.
In IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.
bib | .pdf ]
•   A. Dewan, T. Caselitz, G. D. Tipaldi, and W. Burgard.
Motion-based Detection and Tracking in 3D LiDAR Scans.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Stockholm, Sweden, 2016.
bib | .pdf ]
•   N. Radwan, G. D. Tipaldi, L. Spinello, and W. Burgard.
Do you see the Bakery? Leveraging Geo-Referenced Texts for Global Localization in Public Maps.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Stockholm, Sweden, 2016.
bib | .pdf ]
•   F. Boniardi, A. Valada, W. Burgard, and G. D. Tipaldi.
Autonomous Indoor Robot Navigation Using a Sketch Interface for Drawing Maps and Routes.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Stockholm, Sweden, 2016.
bib | .pdf ]
•   S. Oßwald, M. Bennewitz, W. Burgard, and C. Stachniss.
Speeding-Up Robot Exploration by Exploiting Background Information.
IEEE Robotics and Automation Letters (RA-L), 1(2):716--723, 2016.
bib | DOI | .pdf ]
•   C. Sprunk, B. Lau, P. Pfaff, and W. Burgard.
An Accurate and Efficient Navigation System for Omnidirectional Robots in Industrial Environments.
Autonomous Robots, pages 1--21, 2016.
bib | DOI | .pdf ]
•   H. Kretzschmar, M. Spies, C. Sprunk, and W. Burgard.
Socially Compliant Mobile Robot Navigation via Inverse Reinforcement Learning.
The International Journal of Robotics Research, 2016.
bib | DOI | .pdf ]

2015

•   C. Sprunk.
Highly Accurate Mobile Robot Navigation.
PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, November 2015.
bib | .pdf ]
•   P. Agarwal.
Robust Graph-Based Localization and Mapping.
PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, April 2015.
bib | .pdf ]
•   O. Vysotska, T. Naseer, L. Spinello, W. Burgard, and C. Stachniss.
Efficient and Effective Matching of Image Sequences Under Substantial Appearance Changes Exploiting GPS Priors.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   F. Burget, C. Maurer, W. Burgard, and M. Bennewitz.
Learning motor control parameters for motion strategy analysis of Parkinson's disease patients.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), pages 5019--5025, Hamburg, Germany, 2015.
bib | DOI | .pdf ]
•   A. Eitel, J. T. Springenberg, L. Spinello, M. Riedmiller, and W. Burgard.
Multimodal Deep Learning for Robust RGB-D Object Recognition.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015.
bib | .pdf ]
•   P. Agarwal, W. Burgard, and L. Spinello.
Metric Localization using Google Street View.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015.
bib | .pdf ]
•   B. Behzadian, P. Agarwal, W. Burgard, and G. D. Tipaldi.
Monte Carlo Localization in Hand-Drawn Maps.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015.
bib | .pdf ]
•   A. Wachaja, P. Agarwal, M. Zink, M. Reyes Adame, K. Möller, and W. Burgard.
Navigating Blind People with a Smart Walker.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015.
bib | .pdf ]
•   T. Naseer, M. Ruhnke, L. Spinello, C. Stachniss, and W. Burgard.
Robust Visual SLAM Across Seasons.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2015.
bib | .pdf ]
•   J. Röwekämper, B. Suger, W. Burgard, and G. D. Tipaldi.
Accurate Localization with Respect to Moving Objects via Multiple-Body Registration.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2015.
bib | .pdf ]
•   W. Winterhalter, F. Fleckenstein, B. Steder, L. Spinello, and W. Burgard.
Accurate Indoor Localization for RGB-D Smartphones and Tablets given 2D Floor Plans.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2015.
bib | .pdf ]
•   M. Mazuran, F. Boniardi, W. Burgard, and G. D. Tipaldi.
Relative Topometric Localization in Globally Inconsistent Maps.
In Proc. of the International Symposium on Robotics Research (ISRR), Sestri Levante, 2015.
bib | .pdf ]
•   A. Valada, L. Spinello, and W. Burgard.
Deep Feature Learning for Acoustic-based Terrain Classification.
In Proc. of the International Symposium on Robotics Research (ISRR), Sestri Levante, 2015.
bib | .pdf ]
•   W. Burgard, P. Pfaff, and C. Sprunk. World Robotics 2015 Service Robots: Statistics, Market Analysis, Forecasts, Case Studies, chapter Flexible Autonomous Navigation for Industrial Shop Floor Applications, pages 256--263. International Federation of Robotics (IFR), Statistical Department, 2015.
bib ]
•   M. Kollmitz, K. Hsiao, J. Gaa, and W. Burgard.
Time Dependent Planning on a Layered Social Cost Map for Human-Aware Robot Navigation.
In Proc. of the IEEE European Conference on Mobile Robots (ECMR), Lincoln, 2015.
bib | .pdf ]
•   F. Boniardi, B. Behzadian, W. Burgard, and G. D. Tipaldi.
Robot Navigation in Hand-Drawn Sketched Maps.
In Proc. of the IEEE European Conference on Mobile Robots (ECMR), Lincoln, 2015.
bib | DOI | .pdf ]
•   S. Di Lucia, G. D. Tipaldi, and W. Burgard.
Attitude Stabilization Control of an Aerial Manipulator using a Quaternion-based Backstepping Approach.
In Proc. of the IEEE European Conference on Mobile Robots (ECMR), Lincoln, 2015.
bib | .pdf ]
•   T. Naseer, B. Suger, M. Ruhnke, and W. Burgard.
Vision-Based Markov Localization Across Large Perceptual Changes.
In Proc. of the IEEE European Conference on Mobile Robots (ECMR), Lincoln, 2015.
bib | .pdf ]
•   M. Mazuran, C. Sprunk, W. Burgard, and G. D. Tipaldi.
LexTOR: Lexicographic Teach Optimize and Repeat Based on User Preferences.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Seattle, 2015.
bib | .pdf ]
•   S. Schröer, I. Killmann, B. Frank, M. Völker, L. D. J. Fiederer, T. Ball, and W. Burgard.
An Autonomous Robotic Assistant for Drinking.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   T. Schubert, A. Gkogkidis, T. Ball, and W. Burgard.
Automatic Initialization for Skeleton Tracking in Optical Motion Capture.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 734--739, 2015.
bib | .pdf ]
•   B. Frank, M. Ruhnke, M. Tatarchenko, and W. Burgard.
3D-Reconstruction of Indoor Environments from Human Activity.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   J. Röwekämper, M. Ruhnke, B. Steder, W. Burgard, and G. D. Tipaldi.
Automatic Extrinsic Calibration of Multiple Laser Range Sensors with Little Overlap.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   P. Ruchti, B. Steder, M. Ruhnke, and W. Burgard.
Localization on OpenStreetMap Data using a 3D Laser Scanner.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   B. Suger, B. Steder, and W. Burgard.
Traversability Analysis for Mobile Robots in Outdoor Environments: A Semi-Supervised Learning Approach Based on 3D-Lidar Data.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   B. Steder, M. Ruhnke, R. Kümmerle, and W. Burgard.
Maximum Likelihood Remission Calibration for Groups of Heterogeneous Laser Scanners.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2015.
bib | .pdf ]
•   M. Kuderer, S. Gulati, and W. Burgard.
Learning Driving Styles for Autonomous Vehicles from Demonstration.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, USA, 2015.
bib | .pdf ]
•   N. Abdo, C. Stachniss, L. Spinello, and W. Burgard.
Robot, Organize my Shelves! Tidying up Objects by Predicting User Preferences.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, USA, 2015.
bib | .pdf ]
•   C. Sprunk, J. Roewekaemper, G. Parent, L. Spinello, G. D. Tipaldi, W. Burgard, and M. Jalobeanu.
An Experimental Protocol for Benchmarking Robotic Indoor Navigation.
In M. A. Hsieh, O. Khatib, and V. Kumar, editors, Experimental Robotics, volume 109 of Springer Tracts in Advanced Robotics, pages 487--504. Springer International Publishing, 2015.
bib | DOI | .pdf ]

2014

•   O. Vysotska, B. Frank, I. Ulbert, O. Paul, P. Ruther, C. Stachniss, and W. Burgard.
Automatic Channel Selection and Neural Signal Estimation across Channels of Neural Probes.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1453--1459, Chicago, IL, USA, September 2014.
bib | DOI | .pdf ]
•   P. Agarwal, W. Burgard, and C. Stachniss.
A Survey of Geodetic Approaches to Mapping and the Relationship to Graph-Based SLAM.
Robotics and Automation Magazine, September 2014.
bib | DOI | .pdf ]
•   M. Beinhofer and W. Burgard.
Efficient Estimation of Expected Distributions for Mobile Robot Navigation.
In Proc. of the Austrian Robotics Workshop (ARW), Linz, Austria, May 2014.
bib | .pdf ]
•   S. Oßwald, H. Kretzschmar, W. Burgard, and C. Stachniss.
Learning to Give Route Directions from Human Demonstrations.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), pages 3303--3308, Hong Kong, China, May 2014.
bib | DOI | .pdf ]
•   B. Frank, C. Stachniss, R. Schmedding, M. Teschner, and W. Burgard.
Learning object deformation models for robot motion planning.
Robotics and Autonomous Systems, 62(8):1153--1174, April 2014.
bib | DOI | .pdf ]
•   F. Endres, J. Hess, J. Sturm, D. Cremers, and W. Burgard.
3D Mapping with an RGB-D Camera.
IEEE Trans. on Robotics, 30(1):177--187, February 2014.
bib | DOI | .pdf ]
•   R. Kümmerle, M. Ruhnke, B. Steder, C. Stachniss, and W. Burgard.
Autonomous Robot Navigation in Highly Populated Pedestrian Zones.
Journal of Field Robotics, 2014.
bib | DOI | .pdf ]
•   F. Endres, C. Sprunk, R. Kümmerle, and W. Burgard.
A Catadioptric Extension for RGB-D Cameras.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2014.
bib | DOI | .pdf ]
•   A. Wachaja, P. Agarwal, M. R. Adame, K. Möller, and W. Burgard.
A Navigation Aid for Blind People with Walking Disabilities.
In IROS Workshop on Rehabilitation and Assistive Robotics: Bridging the Gap Between Clinicians and Roboticists, Chicago, USA, 2014.
bib | .pdf ]
•   P. Agarwal, G. Grisetti, G. D. Tipaldi, L. Spinello, W. Burgard, and C. Stachniss.
Experimental Analysis of Dynamic Covariance Scaling for Robust Map Optimization Under Bad Initial Estimates.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.
bib | DOI | .pdf ]
•   P. Agarwal, W. Burgard, and C. Stachniss.
Helmert's and Bowie's Geodetic Mapping Methods and Their Relationship to Graph-Based SLAM.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.
bib | DOI | .pdf ]
•   D. Joho.
Learning and Utilizing Spatial Object Relations for Service Robots.
PhD thesis, Albert-Ludwigs-Universität Freiburg, 2014.
bib | .pdf ]
•   M. Kuderer and W. Burgard.
An Approach to Socially Compliant Leader Following for Mobile Robots.
In Social Robotics, volume 8755 of Lecture Notes in Computer Science, pages 239--248. Springer International Publishing, 2014.
bib | DOI | .pdf ]
•   H. Kretzschmar, M. Kuderer, and W. Burgard.
Learning to Predict Trajectories of Cooperatively Navigating Agents.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.
bib | DOI | .pdf ]
•   M. Kuderer, C. Sprunk, H. Kretzschmar, and W. Burgard.
Online Generation of Homotopically Distinct Navigation Paths.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.
bib | DOI | .pdf ]
•   K. M. Wurm, H. Kretzschmar, R. Kümmerle, C. Stachniss, and W. Burgard.
Identifying Vegetation from Laser Data in Structured Outdoor Environments.
Robotics and Autonomous Systems, 62:675--684, 2014.
bib | DOI | http ]
•   E. Ilg, R. Kümmerle, W. Burgard, and T. Brox.
Reconstruction of Rigid Body Models from Motion Distorted Laser Range Data Using Optical Flow.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Hong Kong, China, 2014.
bib | DOI | .pdf ]
•   M. Mazuran, G. D. Tipaldi, L. Spinello, and W. Burgard.
Nonlinear Graph Sparsification for SLAM.
In Proc. of Robotics: Science and Systems (RSS), Berkeley, 2014.
bib | .pdf ]
•   M. Mazuran, G. D. Tipaldi, L. Spinello, W. Burgard, and C. Stachniss.
A Statistical Measure for Map Consistency in SLAM.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Hong Kong, 2014.
bib | DOI | .pdf ]
•   J. Meyer, M. Kuderer, J. Müller, and W. Burgard.
Online Marker Labeling for Fully Automatic Skeleton Tracking in Optical Motion Caputure.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2014.
bib | DOI | .pdf ]
•   T. Naseer, L. Spinello, W. Burgard, and C. Stachniss.
Robust Visual Robot Localization Across Seasons using Network Flows.
In Proc. of the Conf. of the Association for the Advancement of Artificial Intelligence (AAAI), Quebec, Canada, 2014. In press.
bib | .pdf ]
•   N. Abdo, L. Spinello, W. Burgard, and C. Stachniss.
Inferring What to Imitate in Manipulation Actions by Using a Recommender System.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Hong Kong, China, 2014.
bib | DOI ]
•   S. Ito, F. Endres, M. Kuderer, G. Tipaldi, C. Stachniss, and W. Burgard.
W-RGB-D: Floor-Plan-Based Indoor Global Localization Using a Depth Camera and WiFi.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Hong Kong, China, 2014.
bib | DOI | .pdf ]
•   B. Suger, G. D. Tipaldi, L. Spinello, and W. Burgard.
An Approach to Solving Large-Scale SLAM Problems with a Small Memory Footprint.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2014.
bib | DOI | .pdf ]

2013

•   G. D. Tipaldi, D. Meyer-Delius, and W. Burgard.
Lifelong localization in changing environments.
International Journal of Robotics Research, 32(14), December 2013.
bib | .pdf ]
•   F. Endres, J. Trinkle, and W. Burgard.
Learning the Dynamics of Doors for Robotic Manipulation.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Tokyo, Japan, November 2013.
bib | DOI | .pdf ]
•   M. Beinhofer, J. Müller, A. Krause, and W. Burgard.
Robust Landmark Selection for Mobile Robot Navigation.
In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Tokyo, Japan, November 2013.
bib | DOI | .pdf ]
•   C. Sprunk, G. Tipaldi, A. Cherubini, and W. Burgard.
Lidar-based Teach-and-Repeat of Mobile Robot Trajectories.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Tokyo, Japan, November 2013.
bib | DOI | .pdf ]
•   M. Dakulovic, C. Sprunk, L. Spinello, I. Petrovic, and W. Burgard.
Efficient Navigation for Anyshape Holonomic Mobile Robots in Dynamic Environments.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Tokyo, Japan, November 2013.
bib | DOI | .pdf ]
•   E. Olson and P. Agarwal.
Inference on networks of mixtures for robust robot mapping.
International Journal of Robotics Research, 32(7):826--840, July 2013.
bib | DOI | .pdf ]
•   J. Müller.
Autonomous Navigation for Miniature Indoor Airships.
PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, June 2013.
bib | .pdf ]
•   F. Endres, J. Trinkle, and W. Burgard.
Interactive Perception for Learning the Dynamics of Articulated Objects.
In Proceedings of the ICRA 2013 Mobile Manipulation Workshop on Interactive Perception, Karlsruhe, Germany, May 2013.
bib | .pdf ]
•   P. Agarwal, G. D. Tipaldi, L. Spinello, C. Stachniss, and W. Burgard.
Robust Map Optimization using Dynamic Covariance Scaling.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 2013.
bib | DOI | .pdf ]
•   P. Agarwal, G. D. Tipaldi, L. Spinello, C. Stachniss, and W. Burgard.
Dynamic Covariance Scaling for Robust Robotic Mapping.
In Workshop on robust and Multimodal Inference in Factor Graphs, ICRA, Karlsruhe, Germany, May 2013.
bib | DOI | .pdf ]
•   J. Hess, M. Beinhofer, D. Kuhner, P. Ruchti, and W. Burgard.
Poisson-Driven Dirt Maps for Efficient Robot Cleaning.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 2245--2250, Karlsruhe, Germany, May 2013.
bib | DOI | .pdf ]
•   M. Beinhofer, H. Kretzschmar, and W. Burgard.
Deploying Artificial Landmarks to Foster Data Association in Simultaneous Localization and Mapping.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Karlsruhe, Germany, May 2013.
bib | DOI | .pdf ]
•   J. Meyer, M. Kuderer, J. Müller, and W. Burgard.
Online Marker Labeling for Automatic Skeleton Tracking in Optical Motion Capture.
In Proceedings of the ICRA Workshop on Computational Techniques in Natural Motion Analysis and Reconstruction, Karlsruhe, Germany, May 2013.
bib | .pdf ]
•   R. Kümmerle.
State Estimation and Optimization for Mobile Robot Navigation.
PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, April 2013.
bib | .pdf ]
•   A. Riefert, J. Müller, M. Sauer, W. Burgard, and B. Becker.
Identification of Critical Variables using an FPGA-based Fault Injection Framework.
In Proceedings of the IEEE VLSI Test Symposium (VTS), Berkeley, CA, USA, April 2013.
bib | .pdf ]
•   B. Steder.
Feature-Based 3D Perception for Mobile Robots.
PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, April 2013.
bib | .pdf ]
•   A. Riefert, J. Müller, M. Sauer, W. Burgard, and B. Becker.
Identification of Critical Variables using an FPGA-based Fault Injection Framework.
In Proceedings of the Workshop Testmethoden und Zuverlässigkeit von Schaltungen und Systemen (TUZ), Dresden, Germany, February 2013.
bib | .pdf ]
•   P. Ruchti.
Learning Reactive Robot Navigation Policies from Predictive Trajectory Planning. Master's thesis, University of Freiburg, Department of Computer Science, Autonomous Intelligent Systems Group, Freiburg, 2013.
bib | .pdf ]
•   M. Beinhofer, J. Müller, and W. Burgard.
Effective Landmark Placement for Accurate and Reliable Mobile Robot Navigation.
Robotics and Autonomous Systems (RAS), 61(10):1060 -- 1069, 2013.
bib | DOI | .pdf ]
•   M. Kuderer, H. Kretzschmar, and W. Burgard.
Teaching Mobile Robots to Cooperatively Navigate in Populated Environments.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan, 2013.
bib | DOI | .pdf ]
•   H. Kretzschmar, M. Kuderer, and W. Burgard.
Predicting Human Navigation Behavior via Inverse Reinforcement Learning.
In The 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Princeton, NJ, USA, 2013.
bib ]
•   H. Kretzschmar, M. Kuderer, and W. Burgard.
Learning Navigation Policies from Human Demonstrations.
In Proc. of the Workshop on Inverse Optimal Control & Robotic Learning from Demonstration at Robotics: Science and Systems (RSS), Berlin, Germany, 2013.
bib ]
•   H. Kretzschmar, M. Kuderer, and W. Burgard.
Inferring Navigation Policies for Mobile Robots from Demonstrations.
In Proc. of the Autonomous Learning Workshop at the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.
bib ]
•   N. Abdo, H. Kretzschmar, L. Spinello, and C. Stachniss.
Learning Manipulation Actions from a Few Demonstrations.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.
bib | DOI | .pdf ]
•   R. Kümmerle, M. Ruhnke, B. Steder, C. Stachniss, and W. Burgard.
A Navigation System for Robots Operating in Crowded Urban Environments.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.
bib | .pdf ]
•   F. Höflinger, J. Müller, R. Zhang, W. Burgard, and L. Reindl.
A Wireless Micro Inertial Measurement Unit (IMU).
IEEE Transactions on Instrumentation & Measurement, 2013.
bib | DOI | .pdf ]
•   J. Müller and W. Burgard.
Efficient Probabilistic Localization for Autonomous Indoor Airships using Sonar, Air Flow, and IMU Sensors.
Advanced Robotics, 27(9):711--724, 2013.
bib | DOI | .pdf ]
•   F. Sittel, J. Müller, and W. Burgard.
Computing Velocities and Accelerations from a Pose Time Sequence in Three-dimensional Space.
Technical Report 272, University of Freiburg, Department of Computer Science, 2013.
bib | .pdf ]
•   J. Roewekaemper, G. Tipaldi, and W. Burgard.
Learning to Guide Random Tree Planners in High Dimensional Spaces.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo Big Sight, Japan, 2013.
bib | .pdf ]
•   M. Ruhnke, L. Bo, D. Fox, and W. Burgard.
Compact RGBD Surface Models Based on Sparse Coding.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 2013.
bib | .pdf ]
•   B. Lau, C. Sprunk, and W. Burgard.
Efficient grid-based spatial representations for robot navigation in dynamic environments.
Robotics and Autonomous Systems, 61(10):1116--1130, 2013.
bib | .pdf ]
•   I. Bogoslavskyi, O. Vysotska, J. Serafin, G. Grisetti, and C. Stachniss.
Efficient Traversability Analysis for Mobile Robots using the Kinect Sensor.
In Proc. of the European Conference on Mobile Robots (ECMR), Barcelona, Spain, 2013.
bib | .pdf ]
•   W. Burgard and C. Stachniss.
Gestatten, Obelix!
Forschung -- Das Magazin der Deutschen Forschungsgemeinschaft, 1, 2013. In German, invited.
bib | .pdf ]
•   A. Hornung, K. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard.
OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees.
Autonomous Robots, 34:189--206, 2013.
bib | .pdf ]
•   D. Maier, C. Stachniss, and M. Bennewitz.
Vision-Based Humanoid Navigation Using Self- Supervised Obstacle Detection.
The Int. Journal of Humanoid Robotics (IJHR), 10, 2013.
bib | .pdf ]
•   K. Wurm, C. Dornhege, B. Nebel, W. Burgard, and C. Stachniss.
Coordinating Heterogeneous Teams of Robots using Temporal Symbolic Planning.
Autonomous Robots, 34, 2013.
bib | .pdf ]
•   A. Ahmad, G. D. Tipaldi, P. Lima, and W. Burgard.
Cooperative Robot Localization and Target Tracking based on Least Square Minimization.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2013.
bib | DOI | .pdf ]
•   G. D. Tipaldi, L. Spinello, and W. Burgard.
Geometrical FLIRT Phrases for Large Scale Place Recognition in 2D Range Data.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2013.
bib | DOI | .pdf ]

2012

•   J. Wendeberg, J. Müller, C. Schindelhauer, and W. Burgard.
Robust Tracking of a Mobile Beacon using Time Differences of Arrival with Simultaneous Calibration of Receiver Positions.
In Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sydney, Australia, November 2012.
bib | .pdf ]
•   G. Grisetti, R. Kümmerle, and K. Ni.
Robust Optimization of Factor Graphs by using Condensed Measurements.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Vilamoura, Portugal, October 2012.
bib | DOI | .pdf ]
•   J. Sturm, N. Engelhard, F. Endres, W. Burgard, and D. Cremers.
A Benchmark for the Evaluation of RGB-D SLAM Systems.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Vilamoura, Portugal, October 2012.
bib | DOI | .pdf ]
•   K. M. Wurm.
Techniques for Multi-Robot Coordination and Navigation.
PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, October 2012.
bib | http ]
•   C. Stachniss, K. Schill, and D. Uttal, editors. Spatial Cognition VIII. Springer, August 2012.
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•   D. Meyer-Delius, M. Beinhofer, and W. Burgard.
Occupancy Grid Models for Robot Mapping in Changing Environments.
In Proc. of the AAAI Conf. on Artificial Intelligence (AAAI), Toronto, Canada, July 2012.
bib | .pdf ]
•   F. Endres, J. Hess, and W. Burgard.
Graph-Based Action Models for Human Motion Classification.
In ROBOTIK, May 2012.
bib | .pdf ]
•   F. Endres, J. Hess, N. Engelhard, J. Sturm, and W. Burgard.
6D Visual SLAM for RGB-D Sensors.
at - Automatisierungstechnik, 60:270--278, May 2012.
bib | DOI | .pdf ]
•   F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers, and W. Burgard.
An Evaluation of the RGB-D SLAM System.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), St. Paul, Minnesota, May 2012.
bib | DOI | .pdf ]
•   M. Ruhnke, R. Kümmerle, G. Grisetti, and W. Burgard.
Highly Accurate 3D Surface Models by Sparse Surface Adjustment.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), St. Paul, MN, USA, May 2012.
bib | DOI | .pdf ]
•   C. Sprunk, B. Lau, and W. Burgard.
Improved Non-linear Spline Fitting for Teaching Trajectories to Mobile Robots.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), pages 2068--2073, St. Paul, MN, USA, May 2012.
bib | DOI | .pdf ]
•   J. Müller, O. Paul, and W. Burgard.
Probabilistic Velocity Estimation for Autonomous Miniature Airships using Thermal Air Flow Sensors.
In Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), pages 39--44, Saint Paul, MN, USA, May 2012.
bib | .pdf ]
•   F. Höflinger, J. Müller, M. Törk, L. Reindl, and W. Burgard.
A Wireless Micro Inertial Measurement Unit (IMU).
In Proceedings of the IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pages 2578--2583, Graz, Austria, May 2012.
bib | DOI | .pdf ]
•   S. Grzonka, A. Karwath, F. Dijoux, and W. Burgard.
Activity-based Indoor Mapping and Estimation of Human Trajectories.
IEEE Transactions on Robotics (T-RO), 8(1):234--245, March 2012.
bib | DOI | .pdf ]
•   S. Grzonka, G. Grisetti, and W. Burgard.
A Fully Autonomous Indoor Quadrotor.
IEEE Transactions on Robotics (T-RO), 8(1):90--100, March 2012.
bib | DOI | .pdf ]
•   T. Grundmann, M. Fiegert, and W. Burgard.
Rule Set Based Joint State Update.
In Towards Service Robots for Everyday Environments, pages 301--326. Springer, 2012.
bib ]
•   J. Hess, D. Tipaldi, and W. Burgard.
Null Space Optimization for Effective Coverage of 3D Surfaces using Redundant Manipulators.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1923 --1928, Villamoura, Portugal, 2012.
bib | DOI | .pdf ]
•   D. Joho, G. D. Tipaldi, N. Engelhard, C. Stachniss, and W. Burgard.
Nonparametric Bayesian Models for Unsupervised Scene Analysis and Reconstruction.
In Proc. of Robotics: Science and Systems (RSS), Sydney, Australia, 2012.
bib | .pdf ]
•   D. Joho, G. D. Tipaldi, N. Engelhard, C. Stachniss, and W. Burgard.
Unsupervised Scene Analysis and Reconstruction Using Nonparametric Bayesian Models.
In Proc. of the Workshop on Robots in Clutter at Robotics: Science and Systems (RSS), Sydney, Australia, 2012.
bib ]
•   H. Kretzschmar and C. Stachniss.
Information-Theoretic Compression of Pose Graphs for Laser-Based SLAM.
The International Journal of Robotics Research (IJRR), 31:1219--1230, 2012.
bib | DOI | http ]
•   M. Kuderer, H. Kretzschmar, C. Sprunk, and W. Burgard.
Feature-Based Prediction of Trajectories for Socially Compliant Navigation.
In Proc. of Robotics: Science and Systems (RSS), Sydney, Australia, 2012.
bib | .pdf ]
•   N. Abdo, H. Kretzschmar, and C. Stachniss.
From Low-Level Trajectory Demonstrations to Symbolic Actions for Planning.
In Proc. of the ICAPS Workshop on Combining Task and Motion Planning for Real-World Applications (TAMPRA), Atibaia, São Paulo, Brazil, 2012.
bib | .pdf ]
•   K. M. Wurm, H. Kretzschmar, R. Kümmerle, C. Stachniss, and W. Burgard.
Identifying Vegetation from Laser Data in Structured Outdoor Environments.
Robotics and Autonomous Systems, pages --, 2012. In Press.
bib | DOI | .pdf ]
•   R. Kümmerle, G. Grisetti, and W. Burgard.
Simultaneous Parameter Calibration, Localization, and Mapping.
Advanced Robotics, 26(17):2021--2041, 2012.
bib | DOI | .pdf ]
•   K. O. Arras, B. Lau, S. Grzonka, M. Luber, O. M. Mozos, D. Meyer-Delius, and W. Burgard.
Range-Based People Detection and Tracking for Socially Enabled Service Robots.
In E. Prassler, R. Bischoff, W. Burgard, R. Haschke, M. Hägele, G. Lawitzky, B. Nebel, P. Plöger, U. Reiser, and M. Zöllner, editors, Towards Service Robots for Everyday in Environments, volume 76 of Springer Tracts in Advanced Robotics (STAR), pages 235--280. Springer, 2012.
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•   E. Demeester, E. V. Poorten, A. Hüntemann, J. D. Schutter, M. Hofmann, M. Rooker, G. Kronreif, B. Lau, M. Kuderer, W. Burgard, K. V. A . Gelin, P. V. der Beeten, M. Vereecken, S. Ilsbroukx, A. Fossati, G. Roig, X. Boix, L. V. Gool, H. Fraeyman, L. Broucke, H. Goessaert, and J. Josten.
Robotic ADaptation to Humans Adapting to Robots: Overview of the FP7 project RADHAR.
In International Conference on Systems and Computer Science (ICSCS), 2012.
bib | .pdf ]
•   J. Roewekaemper, C. Sprunk, G. Tipaldi, C. Stachniss, P. Pfaff, and W. Burgard.
On the Position Accuracy of Mobile Robot Localization based on Particle Filters combined with Scan Matching.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3158--3164, Villamoura, Portugal, 2012.
bib | .pdf ]
•   C. Stachniss and W. Burgard.
Particle Filters for Robot Navigation.
Foundations and Trends in Robotics, 3(4):211--282, 2012. Published 2014.
bib | DOI ]
•   G. Grisetti, L. Iocchi, B. Leibe, V. Ziparo, and C. Stachniss.
Digitization of Inaccessible Archeological Sites with Autonomous Mobile Robots.
In Conf. on Robotics Innovation for Cultural Heritage, 2012.
bib ]
•   L. Spinello, C. Stachniss, and W. Burgard.
Scene in the Loop: Towards Adaptation-by- Tracking in RGB-D Data.
In Proc. of the RSS Workshop RGB-D: Advanced Reasoning with Depth Cameras, 2012.
bib | .pdf ]
•   M. Ruhnke, B. Steder, G. Grisetti, and W. Burgard.
3D Environment Modeling Based on Surface Primitives.
Towards Service Robots for Everyday Environments, pages 281--300, 2012.
bib ]
•   G. D. Tipaldi, D. Meyer-Delius, M. Beinhofer, and W. Burgard.
Lifelong Localization and Dynamic Map Estimation in Changing Environments.
In RSS Workshop on Robots in Clutter: Manipulation, Perception and Navigation in Human Environments, 2012.
bib ]
•   A. Cunningham, K. Wurm, W. Burgard, and F. Dellaert.
Fully Distributed Scalable Smoothing and Mapping with Robust Multi-robot Data Association.
In Proc. of the IEEE/RSJ International Conference on Robotics & Automation (ICRA), Saint Paul, MN, USA, 2012.
bib | DOI ]

2011

•   G. Tipaldi, D. Meyer-Delius, M. Beinhofer, and W. Burgard.
Simultaneous Localization and Dynamic State Estimation in Reconfigurable Environments.
In Proc. of the IEEE/RSJ IROS Workshop on Metrics and Methodologies for Autonomous Robot Teams in Logistics (MMART-LoG), San Francisco, USA, October 2011.
bib | .pdf ]
•   R. Kümmerle, G. Grisetti, C. Stachniss, and W. Burgard.
Simultaneous Parameter Calibration, Localization, and Mapping for Robust Service Robotics.
In Proc. of the IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Half Moon Bay, CA, USA, October 2011.
bib | .pdf ]
•   M. Ruhnke, R. Kümmerle, G. Grisetti, and W. Burgard.
Range Sensor Based Model Construction by Sparse Surface Adjustment.
In Proc. of the IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Half Moon Bay, CA, USA, October 2011.
bib | .pdf ]
•   M. Beinhofer, J. Müller, and W. Burgard.
Landmark Placement for Accurate Mobile Robot Navigation.
In Proc. of the European Conf. on Mobile Robots (ECMR), pages 55--60, Örebro, Sweden, September 2011.
bib | .pdf ]
•   R. Kümmerle, G. Grisetti, and W. Burgard.
Simultaneous Calibration, Localization, and Mapping.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, September 2011.
bib | .pdf ]
•   J. Müller, N. Kohler, and W. Burgard.
Autonomous Miniature Blimp Navigation with Online Motion Planning and Re-planning.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4941--4946, San Francisco, CA, USA, September 2011.
bib | .pdf ]
•   K. Wurm, D. Hennes, D. Holz, R. Rusu, C. Stachniss, K. Konolige, and W. Burgard.
Hierarchies of Octrees for Efficient 3D Mapping.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, September 2011.
bib | DOI | .pdf ]
•   D. Meyer-Delius, M. Beinhofer, and W. Burgard.
Grid-Based Models for Dynamic Environments.
Technical report, Dept. of Computer Science, University of Freiburg, July 2011.
bib | .pdf ]
•   M. Sauer, V. Tomashevich, J. Müller, M. Lewis, A. Spilla, I. Polian, B. Becker, and W. Burgard.
An FPGA-Based Framework for Run-time Injection and Analysis of Soft Errors in Microprocessors.
In Proceedings of the IEEE International On-Line Testing Symposium (IOLTS), pages 182--185, Athens, Greece, July 2011.
bib | .pdf ]
•   M. Beinhofer, J. Müller, and W. Burgard.
Near-optimal Landmark Selection for Mobile Robot Navigation.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages 4744--4749, Shanghai, China, May 2011.
bib | DOI | .pdf ]
•   D. Meyer-Delius, M. Beinhofer, A. Kleiner, and W. Burgard.
Using Artificial Landmarks to Reduce the Ambiguity in the Environment of a Mobile Robot.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages 5173--5178, Shanghai, China, May 2011.
bib | DOI | .pdf ]
•   D. Joho, M. Senk, and W. Burgard.
Learning Search Heuristics for Finding Objects in Structured Environments.
Robotics and Autonomous Systems, 59(5):319--328, May 2011.
bib | DOI | .pdf ]
•   R. Kümmerle, G. Grisetti, H. Strasdat, K. Konolige, and W. Burgard.
g2o: A General Framework for Graph Optimization.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Shanghai, China, May 2011.
bib | .pdf ]
•   M. Ruhnke, R. Kümmerle, G. Grisetti, and W. Burgard.
Highly Accurate Maximum Likelihood Laser Mapping by Jointly Optimizing Laser Points and Robot Poses.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Shanghai, China, May 2011.
bib | DOI | .pdf ]
•   C. Sprunk, B. Lau, P. Pfaff, and W. Burgard.
Online Generation of Kinodynamic Trajectories for Non-Circular Omnidirectional Robots.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), pages 72--77, Shanghai, China, May 2011.
bib | DOI | .pdf ]
•   A. Spilla, I. Polian, J. Müller, M. Lewis, V. Tomashevich, B. Becker, and W. Burgard.
Run-time Soft Error Injection and Testing of a Microprocessor using FPGAs.
In Proceedings of the Workshop Testmethoden und Zuverlässigkeit von Schaltungen und Systemen (TUZ), Passau, Germany, February 2011.
bib | .pdf ]
•   S. Grzonka.
Mapping, State Estimation, and Navigation for Quadrotors and Human-Worn Sensor Systems.
PhD thesis, Albert-Ludwigs-University of Freiburg, 2011.
bib | .pdf ]
•   S. Grzonka, B. Steder, and W. Burgard.
3D Place Recognition and Object Detection using a Small-sized Quadrotor.
In Workshop on 3D Exploration, Mapping, and Surveillance with Aerial Robots at Robotics: Science and Systems (RSS), 2011.
bib | .pdf ]
•   S. Bouabdallah, C. Bermes, S. Grzonka, C. Gimkiewicz, A. Brenzikofer, R. Hahn, D. Schafroth, G. Grisetti, W. Burgard, and R. Siegwart.
Towards Palm-Size Autonomous Helicopters.
Journal of Intelligent & Robotic Systems, 61:1--27, 2011.
bib ]
•   C. Stachniss and H. Kretzschmar.
Pose Graph Compression for Laser-Based SLAM.
In Proc. of the International Symposium of Robotics Research (ISRR), Flagstaff, AZ, USA, 2011. Invited presentation.
bib | .pdf ]
•   J. Ziegler, H. Kretzschmar, C. Stachniss, G. Grisetti, and W. Burgard.
Accurate Human Motion Capture in Large Areas by Combining IMU- and Laser-Based People Tracking.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 86--91, San Francisco, CA, USA, 2011.
bib | DOI | .pdf ]
•   H. Kretzschmar, C. Stachniss, and G. Grisetti.
Efficient Information-Theoretic Graph Pruning for Graph-Based SLAM with Laser Range Finders.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 865--871, San Francisco, CA, USA, 2011.
bib | DOI | .pdf ]
•   R. Kümmerle, B. Steder, C. Dornhege, A. Kleiner, G. Grisetti, and W. Burgard.
Large Scale Graph-based SLAM using Aerial Images as Prior Information.
Journal of Autonomous Robots, 30(1):25--39, 2011.
bib | DOI | .pdf ]
•   B. Lau, C. Sprunk, and W. Burgard.
Incremental Updates of Configuration Space Representations for Non-Circular Mobile Robots with 2D, 2.5D, or 3D Obstacle Models.
In European Conference on Mobile Robots (ECMR), pages 49--54, Örebro, Sweden, 2011.
bib | .pdf ]
•   B. Steder, M. Ruhnke, S. Grzonka, and W. Burgard.
Place Recognition in 3D Scans Using a Combination of Bag of Words and Point Feature based Relative Pose Estimation.
In Proc. of the Int. Conf. on Intelligent Robots and Systems (IROS), 2011.
bib | DOI | .pdf ]
•   J. Sturm, C. Stachniss, and W. Burgard.
A Probabilistic Framework for Learning Kinematic Models of Articulated Objects.
Journal on Artificial Intelligence Research, 41:477--526, 2011.
bib | .pdf ]
•   M. Bennewitz, D. Maier, A. Hornung, and C. Stachniss.
Integrated Perception and Navigation in Complex Indoor Environments.
In Proc. of the IEEE-RAS Int. Conf. on Humanoid Robots (HUMANOIDS), 2011. Invited presentation at the workshop on Humanoid service robot navigation in crowded and dynamic environments.
bib ]
•   J. Becker, C. Bersch, D. Pangercic, B. Pitzer, T. Rühr, B. Sankaran, J. Sturm, C. Stachniss, M. Beetz, and W. Burgard.
Mobile Manipulation of Kitchen Containers.
In Proc. of the IROS'11 Workshop on Results, Challenges and Lessons Learned in Advancing Robots with a Common Platform, San Francisco, CA, USA, 2011.
bib | DOI | .pdf ]
•   B. Frank, C. Stachniss, N. Abdo, and W. Burgard.
Efficient Motion Planning for Manipulation Robots in Environments with Deformable Objects.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, 2011.
bib | DOI | .pdf ]
•   B. Frank, C. Stachniss, N. Abdo, and W. Burgard.
Using Gaussian Process Regression for Efficient Motion Planning in Environments with Deformable Objects.
In Proc. of the AAAI-11 Workshop on Automated Action Planning for Autonomous Mobile Robots (PAMR), San Francisco, CA, USA, 2011.
bib | .pdf ]
•   D. Maier, M. Bennewitz, and C. Stachniss.
Self-supervised Obstacle Detection for Humanoid Navigation Using Monocular Vision and Sparse Laser Data.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Shanghai, China, 2011.
bib | DOI | .pdf ]
•   S. Asadi, M. Reggente, C. Stachniss, C. Plagemann, and A. Lilienthal. Intelligent Systems for Machine Olfaction: Tools and Methodologies, chapter Statistical Gas Distribution Modelling using Kernel Methods, pages 153--179. IGI Global, 2011.
bib ]
•   B. Steder, R. B. Rusu, K. Konolige, and W. Burgard.
Point Feature Extraction on 3D Range Scans Taking into Account Object Boundaries.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2011.
bib | DOI | .pdf ]

2010

•   K. Konolige, G. Grisetti, R. Kümmerle, W. Burgard, B. Limketkai, and R. Vincent.
Efficient Sparse Pose Adjustment for 2D Mapping.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, October 2010.
bib | DOI | .pdf ]
•   M. Ruhnke, B. Steder, G. Grisetti, and W. Burgard.
Unsupervised Learning of Compact 3D Models Based on the Detection of Recurrent Structures.
In Proc. of the Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, October 2010.
bib | DOI | .pdf ]
•   K. Wurm, C. Dornhege, P. Eyerich, C. Stachniss, B. Nebel, and W. Burgard.
Coordinated Exploration with Marsupial Teams of Robots using Temporal Symbolic Planning.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, October 2010.
bib | DOI | .pdf ]
•   D. Joho and W. Burgard.
Searching for Objects: Combining Multiple Cues To Object Locations Using a Maximum Entropy Model.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 723--728, Anchorage, AK, USA, May 2010.
bib | DOI | .pdf ]
•   G. Grisetti, R. Kümmerle, C. Stachniss, U. Frese, and C. Hertzberg.
Hierarchical Optimization on Manifolds for Online 2D and 3D Mapping.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Anchorage, AK, USA, May 2010.
bib | DOI | .pdf ]
•   J. Müller, C. Gonsior, and W. Burgard.
Improved Monte Carlo Localization of Autonomous Robots through Simultaneous Estimation of Motion Model Parameters.
In Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), pages 2604--2609, Anchorage, AK, USA, May 2010.
bib | .pdf ]
•   M. Karg, K. Wurm, C. Stachniss, K. Dietmayer, and W. Burgard.
Consistent Mapping of Multistory Buildings by Introducing Global Constraints to Graph-based SLAM.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Anchorage, Alaska, May 2010.
bib | DOI | .pdf ]
•   K. Wurm, A. Hornung, M. Bennewitz, C. Stachniss, and W. Burgard.
OctoMap: A Probabilistic, Flexible, and Compact 3D Map Representation for Robotic Systems.
In Proc. of the ICRA 2010 Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, Anchorage, AK, USA, May 2010.
bib | .pdf ]
•   T. Grundmann, M. Fiegert, and W. Burgard.
Probabilistic rule set joint state update as approximation to the full joint state estimation applied to multi object scene analysis.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2047--2052, 2010.
bib | DOI ]
•   S. Bouabdallah, C. Bermes, S. Grzonka, C. Gimkiewicz, A. Brenzikofer, R. Hahn, D. Schafroth, G. Grisetti, W. Burgard, and R. Siegwart.
Towards Palm-Size Autonomous Helicopters.
In International Conference and Exhibition on Unmanned Areal Vehicles (UAV), 2010.
bib | .pdf ]
•   S. Grzonka, F. Dijoux, A. Karwath, and W. Burgard.
Mapping Indoor Environments Based on Human Activity.
In Proc. IEEE International Conference on Robotics and Automation (ICRA), Anchorage, Ak, USA, 2010.
bib | DOI | .pdf ]
•   H. Kretzschmar, G. Grisetti, and C. Stachniss.
Lifelong Map Learning for Graph-based SLAM in Static Environments.
KI -- K}.
bib | DOI ]
•   G. Grisetti, R. Kümmerle, C. Stachniss, and W. Burgard.
A Tutorial on Graph-Based SLAM.
Intelligent Transportation Systems Magazine, IEEE, 2(4):31--43, 2010.
bib | DOI | .pdf ]
•   B. Lau, K. O. Arras, and W. Burgard.
Multi-model Hypothesis Group Tracking and Group Size Estimation.
International Journal of Social Robotics, Springer, 2(1):19--30, 2010.
bib | http ]
•   B. Lau, C. Sprunk, and W. Burgard.
Improved Updating of Euclidean Distance Maps and Voronoi Diagrams.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 2010.
bib | DOI | .pdf ]
•   M. Cornils, A. Rottmann, and O. Paul.
How to Extract the Sheet Resistance and Hall Mobility From Arbitrarily Shaped Planar Four- Terminal Devices With Extended Contacts.
IEEE Transactions on Electron Devices, 57(9):2087--2097, 2010.
bib ]
•   A. Rottmann and W. Burgard.
Learning Non-stationary System Dynamics Online Using Gaussian Processes.
In Proc. of the German Association for Pattern Recognition (DAGM), pages 192--201, 2010.
bib ]
•   P. Schopp, A. Rottmann, L. Klingbeil, W. Burgard, and Y. Manoli.
Gaussian Process Based State Estimation for a Gyroscope-Free IMU.
In Proc.  of the IEEE Sensors Conference, pages 873--878, 2010.
bib ]
•   W. Burgard, K. Wurm, M. Bennewitz, C. Stachniss, A. Hornung, R. Rusu, and K. Konolige.
Modeling the World Around Us: An Efficient 3D Representation for Personal Robotics.
In Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Taipei, Taiwan, 2010.
bib ]
•   J. Sturm, A. Jain, C. Stachniss, C. Kemp, and W. Burgard.
Robustly Operating Articulated Objects based on Experience.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010.
bib | DOI | .pdf ]
•   B. Frank, R. Schmedding, C. Stachniss, M. Teschner, and W. Burgard.
Learning the Elasticity Parameters of Deformable Objects with a Manipulation Robot.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010.
bib | DOI | .pdf ]
•   A. Hornung, M.Bennewitz, C. Stachniss, H. Strasdat, S. Oßwald, and W. Burgard.
Learning Adaptive Navigation Strategies for Resource-Constrained Systems.
In Proc. of the Int. Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems, Lisbon, Portugal, 2010.
bib | .pdf ]
•   J. Sturm, K. Konolige, C. Stachniss, and W. Burgard.
3D Pose Estimation, Tracking and Model Learning of Articulated Objects from Dense Depth Video using Projected Texture Stereo.
In Proc. of the Workshop RGB-D: Advanced Reasoning with Depth Cameras at Robotics: Science and Systems (RSS), Zaragoza, Spain, 2010.
bib | .pdf ]
•   B. Frank, R. Schmedding, C. Stachniss, M. Teschner, and W. Burgard.
Learning Deformable Object Models for Mobile Robot Path Planning using Depth Cameras and a Manipulation Robot.
In Proc. of the Workshop RGB-D: Advanced Reasoning with Depth Cameras at Robotics: Science and Systems (RSS), Zaragoza, Spain, 2010.
bib | .pdf ]
•   C. Plagemann, C. Stachniss, J. Hess, F. Endres, and N. Franklin.
A Nonparametric Learning Approach to Range Sensing from Omnidirectional Vision.
Robotics and Autonomous Systems, 58:762--772, 2010.
bib ]
•   J. Sturm, K. Konolige, C. Stachniss, and W. Burgard.
Vision-based Detection for Learning Articulation Models of Cabinet Doors and Drawers in Household Environments.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Anchorage, Alaska, 2010.
bib | DOI | .pdf ]
•   J. Müller, C. Stachniss, K. Arras, and W. Burgard.
Socially Inspired Motion Planning for Mobile Robots in Populated Environments.
In Cognitive Systems, Cognitive Systems Monographs. Springer, 2010. In press.
bib ]
•   K. Wurm, C. Stachniss, and G. Grisetti.
Bridging the Gap Between Feature- and Grid- based SLAM.
Robotics and Autonomous Systems, 58(2):140 -- 148, 2010.
bib | DOI | .pdf ]
•   B. Steder, R. B. Rusu, K. Konolige, and W. Burgard.
NARF: 3D Range Image Features for Object Recognition.
In Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010.
bib | .pdf ]
•   B. Steder, G. Grisetti, and W. Burgard.
Robust Place Recognition for 3D Range Data based on Point Features.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2010.
bib | DOI | .pdf ]
•   A. Hornung, K. M. Wurm, and M. Bennewitz.
Humanoid Robot Localization in Complex Indoor Environments.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010.
bib | DOI | .pdf ]
•   D. Meyer-Delius, J. Hess, G. Grisetti, and W. Burgard.
Temporary Maps for Robust Localization in Semi-static Environments.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010.
bib | .pdf ]

2009

•   K. Wurm, R. Kümmerle, C. Stachniss, and W. Burgard.
Improving Robot Navigation in Structured Outdoor Environments by Identifying Vegetation from Laser Data.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009.
bib | DOI | .pdf ]
•   W. Burgard, C. Stachniss, G. Grisetti, B. Steder, R. Kümmerle, C. Dornhege, M. Ruhnke, A. Kleiner, and J. D. Tardós.
A Comparison of SLAM Algorithms Based on a Graph of Relations.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009.
bib | DOI | .pdf ]
•   B. Lau, C. Sprunk, and W. Burgard.
Kinodynamic Motion Planning for Mobile Robots Using Splines.
In IEEE Intl. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009.
bib | DOI | .pdf ]
•   B. Steder, G. Grisetti, M. Van Loock, and W. Burgard.
Robust On-line Model-based Object Detection from Range Images.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009.
bib | DOI | .pdf ]
•   D. Joho, M. Senk, and W. Burgard.
Learning Wayfinding Heuristics Based on Local Information of Object Maps.
In Proceedings of the European Conference on Mobile Robots (ECMR), pages 117--122, Mlini/Dubrovnik, Croatia, September 2009.
bib | .pdf ]
•   R. Kümmerle, B. Steder, C. Dornhege, A. Kleiner, G. Grisetti, and W. Burgard.
Large Scale Graph-based SLAM using Aerial Images as Prior Information.
In Proceedings of Robotics: Science and Systems (RSS), Seattle, WA, USA, June 2009.
bib | .pdf ]
•   D. Joho, C. Plagemann, and W. Burgard.
Modeling RFID Signal Strength and Tag Detection for Localization and Mapping.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 3160--3165, Kobe, Japan, May 2009. to appear.
bib | DOI | .pdf ]
•   R. Kümmerle, D. Hähnel, D. Dolgov, S. Thrun, and W. Burgard.
Autonomous Driving in a Multi-level Parking Structure.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages 3395--3400, Kobe, Japan, May 2009.
bib | .pdf ]
•   J. Müller, A. Rottmann, L. Reindl, and W. Burgard.
A Probabilistic Sonar Sensor Model for Robust Localization of a Small-size Blimp in Indoor Environments using a Particle Filter.
In Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), pages 3589--3594, Kobe, Japan, May 2009.
bib | .pdf ]
•   S. Grzonka, C. Plagemann, G. Grisetti, and W. Burgard.
Look-ahead Proposals for Robust Grid-based SLAM with Rao-Blackwellized Particle Filters.
In International Journal of Robotics Research (IJRR), pages 191--200, February 2009.
bib | .pdf ]
•   A. Hornung, H. Strasdat, M. Bennewitz, and W. Burgard.
Learning Efficient Policies for Vision-based Navigation.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2009.
bib | DOI | .pdf ]
•   C. Eppner, J. Sturm, M. Bennewitz, C. Stachniss, and W. Burgard.
Imitation Learning with Generalized Task Descriptions.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   A. Pretto, E. Menegatti, M. Bennewitz, W. Burgard, and E. Pagello.
A Visual Odometry Framework Robust to Motion Blur.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2009.
bib | DOI | .pdf ]
•   M. Bennewitz, C. Stachniss, S. Behnke, and W. Burgard.
Utilizing Reflection Properties of Surfaces to Improve Mobile Robot Localization.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   S. Grzonka, G. Grisetti, and W. Burgard.
Towards a Navigation System for Autonomous Indoor Flying.
In Proc. IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   R. Kümmerle, B. Steder, C. Dornhege, M. Ruhnke, G. Grisetti, C. Stachniss, and A. Kleiner.
On Measuring the Accuracy of SLAM Algorithms.
Journal of Autonomous Robots, 27(4):387--407, 2009.
bib | DOI | .pdf ]
•   B. Lau, K. O. Arras, and W. Burgard.
Tracking Groups of People with a Multi-Model Hypothesis Tracker.
In International Conference on Robotics and Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   D. Meyer-Delius, J. Sturm, and W. Burgard.
Regression-Based Online Situation Recognition for Vehicular Traffic Scenarios.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, USA, 2009.
bib | .pdf ]
•   D. Meyer-Delius, C. Plagemann, and W. Burgard.
Probabilistic Situation Recognition for Vehicular Traffic Scenarios.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 2009.
bib ]
•   D. Meyer-Delius, C. Plagemann, and W. Burgard.
Probabilistic Situation Recognition and its Application to Vehicular Traffic Situations.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009. to appear.
bib | .pdf ]
•   A. Rottmann and W. Burgard.
Adaptive autonomous control using online value iteration with Gaussian processes.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 2106--2111, 2009.
bib | DOI ]
•   M. Ruhnke, B. Steder, G. Grisetti, and W. Burgard.
Unsupervised Learning of 3D Object Models from Partial Views.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   C. Stachniss.
Spatial Modeling and Robot Navigation.
PhD thesis, University of Freiburg, Department of Computer Science, 2009.
bib | .pdf ]
•   G. Grisetti, C. Stachniss, and W. Burgard.
Non-linear Constraint Network Optimization for Efficient Map Learning.
IEEE Transactions on Intelligent Transportation Systems, 10(3):428--439, 2009.
bib | .pdf ]
•   A. Schneider, J. S. C. Stachniss, M. Reisert, H. Burkhardt, and W. Burgard.
Object Identification with Tactile Sensors Using Bag-of-Features.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2009.
bib | DOI | .pdf ]
•   F. Endres, C. Plagemann, C. Stachniss, and W. Burgard.
Scene Analysis using Latent Dirichlet Allocation.
In Proc. of Robotics: Science and Systems (RSS), Seattle, WA, USA, 2009.
bib | .pdf ]
•   F. Endres, J. Hess, N. Franklin, C. Plagemann, C. Stachniss, and W. Burgard.
Estimating Range Information from Monocular Vision.
In Workshop Regression in Robotics - Approaches and Applications at Robotics: Science and Systems (RSS), Seattle, WA, USA, 2009.
bib | .pdf ]
•   J. Sturm, V. Predeap, C. Stachniss, C. Plagemann, K. Konolige, and W. Burgard.
Learning Kinematic Models for Articulated Objects.
In Proc. of the Int. Conf. on Artificial Intelligence (IJCAI), Pasadena, CA, USA, 2009.
bib | .pdf ]
•   J. Sturm, C. Stachniss, V. Predeap, C. Plagemann, K. Konolige, and W. Burgard.
Learning Kinematic Models for Articulated Objects.
In Online Proc. of the Learning Workshop (Snowbird), Clearwater, FL, USA, 2009.
bib | .pdf ]
•   C. Stachniss, C. Plagemann, and A. Lilienthal.
Gas Distribution Modeling using Sparse Gaussian Process Mixtures.
Autonomous Robots, 26:187ff, 2009.
bib | .pdf ]
•   C. Stachniss. Robotic Mapping and Exploration, volume 55 of STAR Springer tracts in advanced robotics. Springer, 2009.
bib ]
•   H. Strasdat, C. Stachniss, and W. Burgard.
Which Landmark is Useful? Learning Selection Policies for Navigation in Unknown Environments.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   B. Frank, C. Stachniss, R. Schmedding, W. Burgard, and M. Teschner.
Real-world Robot Navigation amongst Deformable Obstacles.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009.
bib | DOI | .pdf ]
•   H. Schulz, L. Ott, J. Sturm, and W. Burgard.
Learning Kinematics from Direct Self- Observation Using Nearest-Neighbor Methods.
In Proc. of the German Workshop on Robotics, 2009.
bib | .pdf ]
•   J. Sturm, C. Stachniss, V. Pradeep, C. Plagemann, K. Konolige, and W. Burgard.
Towards Understanding Articulated Objects.
In Proc. of the Workshop on Robot Manipulation at Robotics: Science and Systems Conference (RSS), Seattle, WA, USA, 2009.
bib | .pdf ]
•   J. Sturm, C. Plagemann, and W. Burgard.
Body schema learning for robotic manipulators from visual self-perception.
Journal of Physiology-Paris, 103(3-5):220--231, 2009. Neurorobotics.
bib | DOI | http ]

2008

•   C. Plagemann.
Gaussian Processes for Flexible Robot Learning.
PhD thesis, University of Freiburg, Department of Computer Science, December 2008.
bib | .pdf ]
•   B. Steder, G. Grisetti, C. Stachniss, and W. Burgard.
Visual SLAM for Flying Vehicles.
IEEE Transactions on Robotics, 24(5):1088--1093, November 2008.
bib | DOI | .pdf ]
•   K. Wurm, C. Stachniss, and W. Burgard.
Coordinated Multi-Robot Exploration using a Segmentation of the Environment.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Nice, France, September 2008.
bib | DOI | .pdf ]
•   O. M. Mozos.
Semantic Place Labeling with Mobile Robots.
PhD thesis, University of Freiburg, Freiburg, Germany, July 2008.
bib | .pdf ]
•   H. Zender, O. M. Mozos, P. Jensfelt, G.-J. M. Kruijff, and W. Burgard.
Conceptual Spatial Representations for Indoor Mobile Robots.
Robotics and Autonomous Systems, 56(6):493--502, June 2008.
bib | DOI | .pdf ]
•   R. Kümmerle, R. Triebel, P. Pfaff, and W. Burgard.
Monte Carlo Localization in Outdoor Terrains using Multilevel Surface Maps.
Journal of Field Robotics (JFR), 25:346--359, June - July 2008.
bib | DOI | .pdf ]
•   C. Stachniss, C. Plagemann, A. Lilienthal, and W. Burgard.
Gas Distribution Modeling Using Sparse Gaussian Process Mixture Models.
In Robotics: Science and Systems (RSS), Zurich, Switzerland, June 2008. To appear.
bib | .pdf ]
•   M. Luber, K. Arras, C. Plagemann, and W. Burgard.
Tracking and Classification of Dynamic Objects: An Unsupervised Learning Approach.
In Robotics: Science and Systems (RSS), Zurich, Switzerland, June 2008.
bib ]
•   J. Sturm, C. Plagemann, and W. Burgard.
Adaptive Body Scheme Models for Robust Robotic Manipulation.
In Robotics: Science and Systems (RSS), Zurich, Switzerland, June 2008.
bib | .pdf ]
•   J. Sturm, C. Plagemann, and W. Burgard.
Body Scheme Learning and Life-Long Adaptation for Robotic Manipulation.
In Proceedings of the Workshop on Robot Manipulation at Robotics: Science and Systems Conference (RSS), Zurich, Switzerland, June 2008.
bib | .pdf ]
•   A. Pronobis, O. Martinez Mozos, and B. Caputo.
SVM-based Discriminative Accumulation Scheme for Place Recognition.
In Proceedings of the IEEE International Conference on Robotics and Automation, pages 522--529, Pasadena, CA, USA, May 2008.
bib | DOI | .pdf ]
•   J. Müller, C. Stachniss, K. Arras, and W. Burgard.
Socially Inspired Motion Planning for Mobile Robots in Populated Environments.
In Proceedings of the International Conference on Cognitive Systems (CogSys), pages 85--90, Karlsruhe, Germany, April 2008.
bib | .pdf ]
•   W. Burgard, O. Brock, and C. Stachniss, editors. Robotics: Science and Systems III. MIT Press, March 2008. In press.
bib ]
•   C. Stachniss, O. M. Mozos, and W. Burgard.
Efficient Exploration of Unknown Indoor Environments using a Team of Mobile Robots.
Annals of Mathematics and Artificial Intelligence, 52:205ff, 2008. To appear.
bib | .pdf ]
•   R. Triebel, O. Mozos, and W. Burgard. Studies in Classification, Data Analysis, and Knowledge Organization, chapter Relational Learning in Mobile Robotics: An Application to Semantic Labeling of Objects in 2D and 3D Environment Maps, pages 293--300. Springer-Verlag, 2008.
bib | .pdf ]
•   T. Axenbeck, M. Bennewitz, S. Behnke, and W. Burgard.
Recognizing Complex, Parameterized Gestures from Monocular Image Sequences.
In Proc. of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2008.
bib | .pdf ]
•   C. Stachniss, M. Bennewitz, G. Grisetti, S. Behnke, and W. Burgard.
How to Learn Accurate Grid Maps with a Humanoid.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008.
bib | DOI | .pdf ]
•   M. Bennewitz, T. Axenbeck, S. Behnke, and W. Burgard.
Robust Recognition of Complex Gestures for Natural Human-Robot Interaction.
In Proc. of the Workshop on Interactive Robot Learning at Robotics: Science and Systems Conference (RSS), 2008.
bib ]
•   S. Grzonka, G. Grisetti, and W. Burgard.
Autonomous Indoors Navigation using a Small- Size Quadrotor.
In Workshop Proc. of Intl. Conf. on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR), Venice, Italy, 2008.
bib | .pdf ]
•   S. Grzonka, S. Bouabdallah, G. Grisetti, W. Burgard, and R. Siegwart.
Towards a Fully Autonomous Indoor Helicopter.
In Workshop of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008.
bib | .pdf ]
•   K. Arras, S. Grzonka, M. Luber, and W. Burgard.
Efficient People Tracking in Laser Range Data using a Multi-Hypothesis Leg-Tracker with Adaptive Occlusion Probabilities.
In Proc. IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA, 2008.
bib | DOI | .pdf ]
•   B. Steder, G. Grisetti, S. Grzonka, C. Stachniss, and W. Burgard.
Estimating Consistent Elevation Maps using Down-Looking Cameras and Inertial Sensors.
In Proc. of the Workshop on Robotic Perception on the International Conference on Computer Vision Theory and Applications, Funchal, Madeira, Portugal, 2008.
bib | .pdf ]
•   H. Kretzschmar, C. Stachniss, C. Plagemann, and W. Burgard.
Estimating Landmark Locations from Geo- Referenced Photographs.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2902--2907, Nice, France, 2008.
bib | DOI | .pdf ]
•   P. Pfaff, C. Plagemann, and W. Burgard.
Gaussian Mixture Models for Probabilistic Localization.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. to appear.
bib | DOI | .pdf ]
•   P. Pfaff, C. Stachniss, C. Plagemann, and W. Burgard.
Efficiently Learning High-dimensional Observation Models for Monte-Carlo Localization using Gaussian Mixtures.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Nice, France, 2008.
bib | DOI | .pdf ]
•   C. Plagemann, K. Kersting, and W. Burgard.
Nonstationary Gaussian Process Regression using Point Estimates of Local Smoothness.
In Proc. of the European Conference on Machine Learning (ECML), Antwerp, Belgium, 2008.
bib | .pdf ]
•   W. Burgard, R. Dillmann, C. Plagemann, and N. Vahrenkamp, editors.
Proc. of the 10th International Conference on Intelligent Autonomous Systems, Baden-Baden, Germany, July 23-25, 2008. IOS Press, 2008.
bib ]
•   C. Plagemann, S. Mischke, S. Prentice, K. Kersting, N. Roy, and W. Burgard.
Learning Predictive Terrain Models for Legged Robot Locomotion.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008.
bib | DOI | .pdf ]
•   U. Reiser, C. Mies, and C. Plagemann.
Verteilte Software-Entwicklung in der Robotik - ein Integrations- und Testframework.
In Robotik, Munich, Germany, 2008. In German.
bib ]
•   C. Plagemann, F. Endres, J. Hess, C. Stachniss, and W. Burgard.
Monocular Range Sensing: A Non-Parametric Learning Approach.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008.
bib | DOI | .pdf ]
•   G. Grisetti, D. Lordi Rizzini, C. Stachniss, E. Olson, and W. Burgard.
Online Constraint Network Optimization for Efficient Maximum Likelihood Map Learning.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008.
bib | DOI | .pdf ]
•   B. Frank, M. Becker, C. Stachniss, M. Teschner, and W. Burgard.
Efficient Path Planning for Mobile Robots in Environments with Deformable Objects.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008.
bib | DOI | .pdf ]
•   B. Frank, M. Becker, C. Stachniss, M. Teschner, and W. Burgard.
Learning Cost Functions for Mobile Robot Navigation in Environments with Deformable Objects.
In Workshop on Path Planning on Cost Maps at the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008.
bib | .pdf ]
•   B. Steder, G. Grisetti, C. Stachniss, and W. Burgard.
Learning Visual Maps using Cameras and Inertial Sensors.
In Workshop on Robotic Perception, International Conference on Computer Vision Theory and Applications, Funchal, Madeira, Portugal, 2008. To appear.
bib ]
•   J. Sturm, C. Plagemann, and W. Burgard.
Unsupervised Body Scheme Learning through Self- Perception.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 3328--3333, Pasadena, CA, USA, 2008.
bib | DOI | .pdf ]

2007

•   P. Pfaff, R. Kümmerle, D. Joho, C. Stachniss, R. Triebel, and W. Burgard.
Navigation in Combined Outdoor and Indoor Environments using Multi-Level Surface Maps.
In Proc. of the Workshop on Safe Navigation in Open and Dynamic Environments at the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), San Diego, CA, USA, October 2007.
bib | .pdf ]
•   D. Joho, C. Stachniss, P. Pfaff, and W. Burgard.
Autonomous Exploration for 3D Map Learning.
In K. Berns and T. Luksch, editors, Autonome Mobile Systeme (AMS), pages 22--28, Kaiserslautern, Germany, October 2007. Springer.
bib | DOI | .pdf ]
•   R. Kümmerle, P. Pfaff, R. Triebel, and W. Burgard.
Active Monte Carlo Localization in Outdoor Terrains using Multi-Level Surface Maps.
In K. Berns and T. Luksch, editors, Fachgespräch Autonome Mobile Systeme (AMS), pages 22--28, Kaiserslautern, Germany, October 2007. Springer.
bib | .pdf ]
•   K. Kersting, C. Plagemann, A. Cocora, W. Burgard, and L. De Raedt.
Learning to Transfer Optimal Navigation Policies.
Advanced Robotics. Special Issue on Imitative Robots, 21(9), September 2007.
bib | .pdf ]
•   K. Wurm, C. Stachniss, G. Grisetti, and W. Burgard.
Improved Simultaneous Localization and Mapping using a Dual Representation of the Environment.
In Proc. of the European Conference on Mobile Robots (ECMR), Freiburg, Germany, September 2007.
bib | .pdf ]
•   S. Grzonka, C. Plagemann, G. Grisetti, and W. Burgard.
Look-ahead Proposals for Robust Grid-based SLAM.
In Proc. of the International Conference on Field and Service Robotics (FSR), Chamonix, France, July 2007.
bib | .pdf ]
•   K. M. Wurm.
Robustes Lernen von Umgebungskarten durch Integration verschiedener Repräsentationen. Master's thesis, Albert-Ludwigs-Universität, Freiburg, July 2007. In German.
bib | .pdf ]
•   C. Plagemann, K. Kersting, P. Pfaff, and W. Burgard.
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders.
In Robotics: Science and Systems (RSS), Atlanta, Georgia, USA, June 2007.
bib | .pdf ]
•   T. Lang, C. Plagemann, and W. Burgard.
Adaptive Non-Stationary Kernel Regression for Terrain Modeling.
In Robotics: Science and Systems (RSS), Atlanta, Georgia, USA, June 2007.
bib | .pdf ]
•   O. M. Mozos, R. Triebel, P. Jensfelt, A. Rottmann, and W. Burgard.
Supervised semantic labeling of places using information extracted from sensor data.
Robotics and Autonomous Systems, 55(5):391--402, May 2007.
bib | .pdf ]
•   C. Plagemann, K. Kersting, P. Pfaff, and W. Burgard.
Heteroscedastic Gaussian Process Regression for Modeling Range Sensors in Mobile Robotics.
In Proc. of the Learning Workshop (Snowbird), San Juan, Puerto Rico, March 2007.
bib | .pdf ]
•   K. Kersting, C. Plagemann, P. Pfaff, and W. Burgard.
Most Likely Heteroscedastic Gaussian Process Regression.
In International Conference on Machine Learning (ICML), Corvallis, Oregon, USA, March 2007.
bib | .pdf ]
•   O. M. Mozos, P. Jensfelt, H. Zender, G.-J. M. Kruijff, and W. Burgard.
From Labels to Semantics: An Integrated System for Conceptual Spatial Representations of Indoor Environments for Mobile Robots.
In Proceedings of the IEEE/RSJ IROS 2007 Workshop: Semantic information in robotics, San Diego, CA, USA, 2007.
bib | .html ]
•   C. Stachniss, G. Grisetti, O. M. Mozos, and W. Burgard.
Efficiently Learning Metric and Topological Maps with Autonomous Service Robots.
it--Information Technology, 49(4):232--237, 2007.
bib | .pdf ]
•   H. Zender, P. Jensfelt, O. M. Mozos, G.-J. M. Kruijff, and W. Burgard.
An Integrated Robotic System for Spatial Understanding and Situated Interaction in Indoor Environments.
In Proceedings of the Conference on Artificial Intelligence, Vancouver, British Columbia, Canada, 2007.
bib | .html ]
•   R. Triebel, O. M. Mozos, and W. Burgard.
Relational Learning in Mobile Robotics: An Application to Semantic Labeling of Objects in 2D and 3D Environment Maps.
In Annual Conference of the German Classification Society on Data Analysis, Machine Learning, and Applications, Freiburg, Germany, 2007.
bib ]
•   O. M. Mozos, P. Jensfelt, H. Zender, G.-J. M. Kruijff, and W. Burgard.
From Labels to Semantics: An Integrated System for Conceptual Spatial Representations of Indoor Environments for Mobile Robots.
In Proceedings of the IEEE ICRA Workshop: Semantic information in robotics, pages 33--40, 2007.
bib | .html ]
•   K. O. Arras, O. M. Mozos, and W. Burgard.
Using Boosted Features for the Detection of People in 2D Range Data.
In Proceedings of the IEEE International Conference on Robotics and Automation, pages 3402--3407, 2007.
bib | DOI | .html ]
•   R. Triebel, R. Schmidt, O. M. Mozos, and W. Burgard.
Instace-based AMN Classification for Improved Object Recognition in 2D and 3D Laser Range Data.
In Proceedings of the International Joint Conference on Artificial Intelligence, pages 2225--2230, Hyderabad, India, 2007.
bib | .pdf ]
•   O. M. Mozos, C. Stachniss, A. Rottmann, and W. Burgard. Robotics Research: Results of the 12th International Symposium ISRR., volume 28 of STAR Springer tracts in advanced robotics, chapter Using AdaBoost for Place Labeling and Topological Map Building., pages 453--472. Springer-Verlag Berlin Heidelberg, Germany, 2007.
bib | .pdf ]
•   H. Strasdat, C. Stachniss, M. Bennewitz, and W. Burgard.
Visual Bearing-Only Simultaneous Localization and Mapping with Improved Feature Matching.
In Proc. of the Fachgespräche Autonome Mobile Systeme (AMS), Kaiserslautern, Germany, 2007.
bib | .pdf ]
•   G. Grisetti, S. Grzonka, C. Stachniss, P. Pfaff, and W. Burgard.
Efficient Estimation of Accurate Maximum Likelihood Maps in 3D.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Diego, CA, USA, 2007.
bib | DOI | .pdf ]
•   S. Steder, G. Grisetti, C. Stachniss, S. Grzonka, A. Rottmann, and W. Burgard.
Learning Maps in 3D using Attitude and Noisy Vision Sensors.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 644--649, San Diego, CA, USA, 2007.
bib | DOI | .pdf ]
•   G. Grisetti, C. Stachniss, S. Grzonka, and Burgard.
A Tree Parameterization for Efficiently Computing Maximum Likelihood Maps using Gradient Descent.
In Proc. of Robotics: Science and Systems (RSS), Atlanta, GA, USA, 2007.
bib | .pdf ]
•   D. Joho.
Exploration für mobile Roboter unter Verwendung dreidimensionaler Umgebungsmodelle. Master's thesis, Albert-Ludwigs-Universität Freiburg, 2007.
bib | .pdf ]
•   R. Kümmerle, R. Triebel, P. Pfaff, and W. Burgard.
Monte Carlo Localization in Outdoor Terrains using Multi-Level Surface Maps.
In Proc. of the International Conference on Field and Service Robotics (FSR), Chamonix, France, 2007.
bib | .pdf ]
•   D. Meyer-Delius and W. Burgard.
Maximum-Likelihood Sample-Based Maps for Mobile Robots.
In Proc. of the European Conference on Mobile Robots (ECMR), Freiburg, Germany, 2007.
bib ]
•   D. Meyer-Delius, C. Plagemann, G. von Wichert, W. Feiten, G. Lawitzky, and W. Burgard.
A Probabilistic Relational Model for Characterizing Situations in Dynamic Multi-Agent Systems.
In In Proc. of the 31th Annual Conference of the German Classification Society on Data Analysis, Machine Learning, and Applications (GFKL), Freiburg, Germany, 2007.
bib | .pdf ]
•   P. Pfaff, C. Triebel, R.and Stachniss, P. Lamon, W. Burgard, and R. Siegwart.
Towards Mapping of Citites.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Rome, Italy, 2007.
bib | DOI | .pdf ]
•   P. Pfaff, C. Plagemann, and W. Burgard.
Improved Likelihood Models for Probabilistic Localization based on Range Scans.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Diego, CA, USA, 2007.
bib | DOI | .pdf ]
•   P. Pfaff, R. Triebel, and W. Burgard.
An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing.
International Journal of Robotics Research, 2007.
bib ]
•   A. Rottmann, C. Plagemann, P. Hilgers, and W. Burgard.
Autonomous Blimp Control using Model-free Reinforcement Learning in a Continuous State and Action Space.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1895--1900, San Diego, CA, USA, 2007.
bib | DOI | .pdf ]
•   C. Plagemann, D. Fox, and W. Burgard.
Efficient Failure Detection on Mobile Robots Using Particle Filters with Gaussian Process Proposals.
In Proc. of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, 2007.
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•   A. Rottmann, M. Sippel, T. Zitterell, W. Burgard, L. Reindl, and C. Scholl.
Towards an Experimental Autonomous Blimp Platform.
In Proc. of the European Conference on Mobile Robots (ECMR), Freiburg, Germany, 2007.
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•   B. Steder, A. Rottmann, G. Grisetti, C. Stachniss, and W. Burgard.
Autonomous Navigation for Small Flying Vehicles.
In Workshop on Micro Aerial Vehicles at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Diego, CA, USA, 2007.
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•   W. Burgard, C. Stachniss, and D. Haehnel.
Mobile Robot Map Learning from Range Data in Dynamic Environments.
In C. Laugier and R. Chatila, editors, Autonomous Navigation in Dynamic Environments, volume 35 of STAR Springer tracts in advanced robotics. Springer, 2007.
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•   C. Stachniss, G. Grisetti, W. Burgard, and N. Roy.
Evaluation of Gaussian Proposal Distributions for Mapping with Rao-Blackwellized Particle Filters.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Diego, CA, USA, 2007.
bib | DOI | .pdf ]
•   O. Martínez-Mozos, C. Stachniss, A. Rottmann, and W. Burgard.
Using AdaBoost for Place Labelling and Topological Map Building.
In S. Thrun, R. Brooks, and H. Durrant-Whyte, editors, Robotics Research, volume 28 of STAR Springer tracts in advanced robotics. Springer, 2007.
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•   G. Grisetti, C. Stachniss, and W. Burgard.
Improved Techniques for Grid Mapping with Rao- Blackwellized Particle Filters.
IEEE Transactions on Robotics, 23(1):34--46, 2007.
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•   G. Grisetti, G. Tipaldi, C. Stachniss, W. Burgard, and D. Nardi.
Fast and Accurate SLAM with Rao-Blackwellized Particle Filters.
Robotics and Autonomous Systems, 55(1):30--38, 2007.
bib | .pdf ]
•   B. Steder.
Techniken für bildbasiertes SLAM unter Verwendung von Lagesensoren. Master's thesis, Albert-Ludwigs-Universität, Freiburg, 2007.
bib | .pdf ]
•   G. D. Tipaldi, G. Grisetti, and W. Burgard.
Approximated Covariance Estimation in Graphical Approaches to SLAM.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Diego, USA, 2007.
bib | DOI | .pdf ]

2006

•   O. M. Mozos, A. Rottmann, R. Triebel, P. Jensfelt, and W. Burgard.
Semantic Labeling of Places using Information Extracted from Laser and Vision Sensor Data.
In Proceedings of the IEEE/RSJ IROS Workshop: From sensors to human spatial concepts, pages 391--402, Beijing, China, 2006.
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•   O. M. Mozos and W. Burgard.
Supervised Learning of Topological Maps using Semantic Information Extracted from Range Data.
In IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, 2006.
bib | DOI | .pdf ]
•   A. Gil, O. Reinoso, W. Burgard, C. Stachniss, and O. M. Mozos.
Improving Data Association in Rao-Blackwellized visual SLAM.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 2076--2081, Beijing, China, 2006.
bib | DOI | .pdf ]
•   C. Stachniss, O. M. Mozos, and W. Burgard.
Speeding-Up Multi-Robot Exploration by Considering Semantic Place Information.
In Proceedings of the IEEE International Conference on Robotics and Automation, pages 1692--1697, Orlando, FL, USA, 2006.
bib | DOI | .pdf ]
•   M. Bennewitz, C. Stachniss, W. Burgard, and S. Behnke.
Metric Localization with Scale-Invariant Visual Features using a Single Perspective Camera.
In H. Christiensen, editor, European Robotics Symposium 2006, volume 22 of STAR Springer tracts in advanced robotics, pages 143--157. Springer Verlag Berlin Heidelberg, Germany, 2006.
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•   G. Sukhatme, S. Schaal, D. Fox, and W. Burgard, editors.
Proc. of the Robotics - Science and Systems (RSS), 2006.
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•   M. Mucientes and W. Burgard.
Multi-Hypothesis Tracking of Clusters of People.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2006.
bib | DOI ]
•   S. Grzonka.
Untersuchungen zur Genauigkeit von SLAM- Verfahren mit Partikel-Filtern. Master's thesis, University of Freiburg, Department of Computer Science, 2006. In German.
bib | .pdf ]
•   P. Lamon, C. Stachniss, R. Triebel, C. Pfaff, P. andPlagemann, G. Grisetti, S. Kolski, W. Burgard, and R. Siegwart.
Mapping with an Autonomous Car.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Beijing, China, 2006.
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•   P. Pfaff, W. Burgard, and D. Fox.
Robust Monte-Carlo Localization using Adaptive Likelihood Models.
In H. Christiensen, editor, European Robotics Symposium 2006, volume 22 of springerstaradvanced, pages 181--194. Springer-Verlag Berlin Heidelberg, Germany, 2006.
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•   R. Triebel, P. Pfaff, and W. Burgard.
Multi Level Surface Maps for Outdoor Terrain Mapping and Loop Closing.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2006.
bib | DOI | .pdf ]
•   A. Cocora, K. Kersting, C. Plagemann, W. Burgard, and L. De Raedt.
Learning Relational Navigation Policies.
KI - Künstliche Intelligenz, Themenheft Lernen und Selbstorganisation von Verhalten, 3:12--18, 2006.
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•   A. Cocora, K. Kersting, C. Plagemann, W. Burgard, and L. De Raedt.
Learning Relational Navigation Policies.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Beijing, China, 2006.
bib | DOI | .pdf ]
•   C. Plagemann, C. Stachniss, and W. Burgard.
Efficient Failure Detection for Mobile Robots using Mixed-Abstraction Particle Filters.
In H. Christensen, editor, European Robotics Symposium 2006, volume 22 of STAR Springer tracts in advanced robotics, pages 93--107. Springer-Verlag Berlin Heidelberg, Germany, 2006.
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•   A. Arturo Gil, O. Reinoso, C. Fernández, M. Asunción Vicente, A. Rottmann, and O. Martínez Mozos.
Simultaneous localization and mapping in unmodified environments using stereo vision.
In Proc. of the Int. Conf. on Informatics in Control, Automation, and Robotics, pages 302--309, 2006.
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•   D. Meier, C. Stachniss, and W. Burgard.
Cooperative Exploration With Multiple Robots Using Low Bandwidth Communication.
In J. Beyerer, F. Puente León, and K.-D. Sommer, editors, Informationsfusion in der Mess- und Sensortechnik, pages 145--157, 2006.
bib | .pdf ]
•   A. Gil, O. Reinoso, O. Martínez-Mozos, C. Stachniss, and W. Burgard.
Improving Data Association in Vision-based SLAM.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Beijing, China, 2006.
bib | DOI ]
•   D. Sonntag, S. Stachniss-Carp, C. Stachniss, and V. Stachniss.
Determination of Root Canal Curvatures before and after Canal Preparation (Part II): A Method based on Numeric Calculus.
Aust Endod J, 32:16--25, 2006.
bib | .pdf ]
•   C. Stachniss.
Exploration and Mapping with Mobile Robots.
PhD thesis, University of Freiburg, Department of Computer Science, 2006.
bib | .pdf ]
•   G. Grisetti, G. Tipaldi, C. Stachniss, W. Burgard, and D. Nardi.
Speeding-Up Rao-Blackwellized SLAM.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 442--447, Orlando, FL, USA, 2006.
bib | DOI | .pdf ]

2005

•   C. Stachniss, O. M. Mozos, A. Rottmann, and W. Burgard.
Semantic Labeling of Places.
In International Symposium of Robotics Research, San Francisco, CA, USA, October 2005.
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•   A. Rottmann, O. M. Mozos, C. Stachniss, and W. Burgard.
Semantic Place Classification of Indoor Environments with Mobile Robots using Boosting.
In Proceedings of the National Conference on Artificial Intelligence, pages 1306--1311, Pittsburgh, PA, USA, 2005.
bib | .pdf ]
•   O. M. Mozos, C. Stachniss, and W. Burgard.
Supervised Learning of Places from Range Data using AdaBoost.
In Proceedings of the IEEE International Conference on Robotics and Automation, pages 1742--1747, Barcelona, Spain, 2005.
bib | DOI | .pdf ]
•   M. Bennewitz and W. Burgard.
Serviceroboter für den Pflegebereich.
In A. M. Raem, H. Fenger, G. F. Kolb, T. Nikolaus, L. Pientka, R. Rychlik, and T. Vömel, editors, Handbuch Geriatrie. Lehrbuch fr Praxis und Klinik. Deutsche Krankenhaus Verlagsgesellschaft mbH, Düsseldorf, 2005. In German.
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•   M. Bennewitz, W. Burgard, G. Cielniak, and S. Thrun.
Learning Motion Patterns of People for Compliant Robot Motion.
The International Journal of Robotics Research (IJRR), 24(1), 2005.
bib | .pdf ]
•   H. Choset, K. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. Kavraki, and S. Thrun. Principles of Robot Motion: Theory, Algorithms and Implementation. MIT Press, 2005.
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•   S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics. MIT Press, 2005.
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•   S. Thrun, S. Thayer, W. Whittaker, C. Baker, W. Burgard, D. Ferguson, D. Hähnel, M. Montemerlo, A. Morris, Z. Omohundro, C. Reverte, and W. Whittaker.
Autonomous Exploration and Mapping of Abandoned Mines.
IEEE Robotics & Automation Magazine, 11(4), 2005.
bib | .pdf ]
•   J. Wolf, W. Burgard, and H. Burkhardt.
Robust Vision-based Localization by Combining an Image Retrieval System with Monte Carlo Localization.
IEEE Transactions on Robotics, 21(2):208--216, 2005.
bib | .pdf ]
•   P. Pfaff and W. Burgard.
An Efficient Extension of Elevation Maps for Outdoor Terrain Mapping.
In Proc. of the International Conference on Field and Service Robotics (FSR), pages 165--176, Port Douglas, QLD, Australia, 2005.
bib | .pdf ]
•   C. Plagemann and W. Burgard.
Sequential Parameter Estimation for Fault Diagnosis in Mobile Robots Using Particle Filters.
In Autonome Mobile Systeme 2005 (AMS), pages 197--202. Springer, 2005.
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•   C. Plagemann, T. Müller, and W. Burgard.
Vision-Based 3D Object Localization Using Probabilistic Models of Appearance.
In W. G. Kropatsch, R. Sablatnig, and A. Hanbury, editors, Pattern Recognition, 27th DAGM Symposium, Vienna, Austria, volume 3663 of Lecture Notes in Computer Science, pages 184--191. Springer, 2005.
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•   A. Rottmann.
Bild- und laserbasierte Klassifikation von Umgebungen mit mobilen Robotern. Master's thesis, University of Freiburg, Department of Computer Science, 2005. In German.
bib | .pdf ]
•   C. Stachniss, D. Hähnel, W. Burgard, and G. Grisetti.
On Actively Closing Loops in Grid-based FastSLAM.
Advanced Robotics, 19(10):1059--1080, 2005.
bib | .pdf ]
•   C. Stachniss, G. Grisetti, and W. Burgard.
Information Gain-based Exploration Using Rao- Blackwellized Particle Filters.
In Proc. of Robotics: Science and Systems (RSS), pages 65--72, Cambridge, MA, USA, 2005.
bib | .pdf ]
•   D. Meier, C. Stachniss, and W. Burgard.
Coordinating Multiple Robots During Exploration Under Communication With Limited Bandwidth.
In Proc. of the European Conference on Mobile Robots (ECMR), pages 26--31, Ancona, Italy, 2005.
bib | .pdf ]
•   C. Stachniss and W. Burgard.
Mobile Robot Mapping and Localization in Non-Static Environments.
In Proc. of the National Conf. on Artificial Intelligence (AAAI), pages 1324--1329, Pittsburgh, PA, USA, 2005.
bib | .pdf ]
•   P. Trahanias, W. Burgard, A. Argyros, D. Hähnel, H. Baltzakis, P. Pfaff, and C. Stachniss.
TOURBOT and WebFAIR: Web-Operated Mobile Robots for Tele-Presence in Populated Exhibitions.
IEEE Robotics & Automation Magazine, 12(2):77--89, 2005.
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•   W. Burgard, M. Moors, C. Stachniss, and F. Schneider.
Coordinated Multi-Robot Exploration.
IEEE Transactions on Robotics, 21(3):376--386, 2005.
bib | DOI | .pdf ]
•   W. Burgard, C. Stachniss, and G. Grisetti.
Information Gain-based Exploration Using Rao- Blackwellized Particle Filters.
In Proc. of the Learning Workshop (Snowbird), Snowbird, UT, USA, 2005.
bib | .pdf ]
•   C. Stachniss, G. Grisetti, and W. Burgard.
Recovering Particle Diversity in a Rao-Blackwellized Particle Filter for SLAM after Actively Closing Loops.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 667--672, Barcelona, Spain, 2005.
bib | DOI | .pdf ]
•   G. Grisetti, C. Stachniss, and W. Burgard.
Improving Grid-based SLAM with Rao- Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling.
In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 2443--2448, Barcelona, Spain, 2005.
bib | DOI | .pdf ]
•   R. Triebel and W. Burgard.
Improving Simultaneous Localization and Mapping in 3D Using Global Constraints.
In Proc. of the Conf. of the Association for the Advancement of Artificial Intelligence (AAAI), 2005.
bib | .pdf ]
•   R. Triebel, W. Burgard, and F. Dellaert.
Using Hierarchical EM to Extract Planes from 3D Range Scans.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2005.
bib | DOI | .pdf ]
•   D. Wolf, G. Sukhatme, D. Fox, and W. Burgard.
Autonomous Terrain Mapping and Classification Using Hidden Markov Models.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2005.
bib | DOI | .pdf ]

2004

•   O. M. Mozos.
Supervised Learning of Places from Range Data using AdaBoost. Master's thesis, University of Freiburg, December 2004.
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•   M. Bennewitz.
Mobile Robot Navigation in Dynamic Environments.
PhD thesis, University of Freiburg, Department of Computer Science, 2004.
bib | .pdf ]
•   M. Bennewitz, J. Pastrana, and W. Burgard.
Active Localization of Persons with a Mobile Robot Based on Learned Motion Behaviors.
In Proc. of the third Workshop on Selforganization of Adaptive Behavior (SOAVE), 2004.
bib | .pdf ]
•   S. Thrun, C. Martin, Y. Liu, D. Hähnel, R. Emery Montemerlo, C. Deepayan, and W. Burgard.
A Real-Time Expectation Maximization Algorithm for Acquiring Multi-Planar Maps of Indoor Environments with Mobile Robots.
IEEE Transactions on Robotics and Automation, 20(3):433--442, 2004.
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•   D. Hähnel, W. Burgard, D. Fox, K. Fishkin, and M. Philipose.
Mapping and Localization with RFID Technology.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2004.
bib | .pdf ]
•   D. Sack and W. Burgard.
A Comparison of Methods for Line Extraction from Range Data.
In Proc. of the IVAC Symposium on Intelligent Autonomous Vehicles (IAV), 2004.
bib | .pdf ]
•   M. Veeck and W. Burgard.
Learning Polyline Maps from Range Scan Data Acquired with Mobile Robots.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2004.
bib | .pdf ]
•   C. Plagemann.
Ansichtsbasierte Erkennung und Lokalisierung von Objekten zur Initialisierung eines Verfolgungsprozesses. Master's thesis, University of Karlsruhe, Department of Computer Science and Fraunhofer Institute IITB, Karlsruhe, 2004. In German.
bib | .pdf ]
•   C. Stachniss, G. Grisetti, D. Hähnel, and W. Burgard.
Improved Rao-Blackwellized Mapping by Adaptive Sampling and Active Loop-Closure.
In Proc. of the Workshop on Self-Organization of AdaptiVE behavior (SOAVE), pages 1--15, Ilmenau, Germany, 2004.
bib | .pdf ]
•   C. Stachniss, D. Hähnel, and W. Burgard.
Exploration with Active Loop-Closing for FastSLAM.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pages 1505--1510, Sendai, Japan, 2004.
bib | DOI | .pdf ]

2003

•   G. Cielniak, M. Bennewitz, and W. Burgard.
Robust Localization of Persons Based on Learned Motion Patterns.
In Proc. of the European Conference on Mobile Robots (ECMR), 2003.
bib | .pdf ]
•   G. Cielniak, M. Bennewitz, and W. Burgard.
Where is ...? Learning and Utilizing Motion Patterns of Persons with Mobile Robots.
In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), 2003.
bib | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Adapting Navigation Strategies Using Motions Patterns of People.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2003.
bib | DOI | .pdf ]
•   M. Bennewitz, G. Cielniak, and W. Burgard.
Utilizing Learned Motion Patterns to Robustly Track Persons.
In Proc. of the Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS), 2003.
bib | .pdf ]
•   J. Blanco, W. Burgard, R. Sanz, and J. Fernandez.
Fast Face Detection for Mobile Robots by Integrating Laser Range Data with Vision.
In Proc. of the International Conference on Advanced Robotics (ICAR), 2003.
bib | .pdf ]
•   W. Burgard, P. Trahanias, D. Hähnel, M. Moors, D. Schulz, H. Baltzakis, and A. Argyros.
Tele-presence in Populated Exhibitions through Web-operated Mobile Robots.
Journal of Autonomous Robots, 15:299--316, 2003.
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•   A. Borkowski, W. Burgard, and P. Zingaretti, editors.
Proc. of the first European Conference on Mobile Robots (ECMR), 2003.
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•   D. Hähnel, W. Burgard, and S. Thrun.
Learning compact 3D models of indoor and outdoor environments with a mobile robot.
Robotics and Autonomous Systems, 44(1):15--27, 2003.
bib | .pdf ]
•   D. Hähnel, R. Triebel, W. Burgard, and S. Thrun.
Map Building with Mobile Robots in Dynamic Environments.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2003.
bib | .pdf ]
•   D. Hähnel, S. Thrun, and W. Burgard.
An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots.
In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), 2003.
bib | .pdf ]
•   D. Hähnel, D. Schulz, and W. Burgard.
Mobile Robot Mapping in Populated Environments.
Journal of the Robotics Society of Japan (JRSJ), 7(17):579--598, 2003.
bib | .pdf ]
•   D. Schulz, W. Burgard, and A. Fox, D. Cremers.
People Tracking with a Mobile Robot Using Sample-based Joint Probabilistic Data Association Filters.
International Journal of Robotics Research (IJRR), 22(2):99--116, 2003.
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•   S. Thrun, D. Ferguson, D. Hähnel, M. Montemerlo, R. Triebel, and W. Burgard.
A System for Volumetric Robotic Mapping of Abandoned Mines.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2003.
bib | DOI | .pdf ]
•   P. Trahanias, W. Burgard, D. Hähnel, M. Moors, D. Schulz, H. Baltzakis, and A. Argyros.
Interactive Tele-presence in Populated Exhibitions through Web-operated Robots.
In Proc. of the International Conference on Advanced Robotics (ICAR), 2003.
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•   D. Ferguson, A. Morris, D. Hähnel, C. Baker, Z. Omohundro, C. Reverte, S. Thayer, W. Whittaker, W. Burgard, and S. Thrun.
An Autonomous Robotic System for Mapping Abandoned Mines.
In Proc. of the Conference on Neural Information Processing (NIPS), 2003.
bib | .pdf ]
•   D. Hähnel, W. Burgard, D. Fox, and S. Thrun.
A highly efficient FastSLAM algorithm for generating cyclic maps of large-scale environments from raw laser range measurements.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2003.
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•   D. Hähnel, S. Thrun, B. Wegbreit, and W. Burgard.
Towards Lazy Data Association in SLAM.
In Proc. of the Int. Symposium of Robotics Research (ISRR), 2003.
bib | .pdf ]
•   C. Stachniss, D. Hähnel, and W. Burgard.
Grid-based FastSLAM and Exploration with Active Loop Closing.
In Online Proc. of the Dagstuhl Seminar on Robot Navigation (Dagstuhl Seminar 03501), Dagstuhl, Germany, 2003.
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•   C. Stachniss and W. Burgard.
Mapping and Exploration with Mobile Robots using Coverage Maps.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pages 476--481, Las Vegas, NV, USA, 2003.
bib | DOI | .pdf ]
•   C. Stachniss and W. Burgard.
Using Coverage Maps to Represent the Environment of Mobile Robots.
In Proc. of the European Conference on Mobile Robots (ECMR), pages 59--64, Radziejowice, Poland, 2003.
bib | .pdf ]
•   C. Stachniss and W. Burgard.
Exploring Unknown Environments with Mobile Robots using Coverage Maps.
In Proc. of the Int. Conf. on Artificial Intelligence (IJCAI), pages 1127--1132, Acapulco, Mexico, 2003.
bib | .pdf ]

2002

•   M. Bennewitz, W. Burgard, and S. Thrun.
Finding and Optimizing Solvable Priority Schemes for Decoupled Path Planning Techniques for Teams of Mobile Robots.
Robotics and Autonomous Systems, 41, 2002.
bib | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Using EM to Learn Motion Behaviors of Persons with Mobile Robots.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2002.
bib | DOI | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Learning Motion Patterns of Persons for Mobile Service Robots.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2002.
bib | DOI | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Learning Motion Patterns of Persons for Mobile Service Robots.
In Proc. of the VDI-Conference Robotik 2002 (Robotik), 2002.
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•   W. Burgard, M. Moors, and F. Schneider.
Collaborative Exploration of Unknown Environments with Teams of Mobile Robots.
In M. Beetz, J. Hertzberg, M. Ghallab, and M. Pollack, editors, Advances in Plan-Based Control of Robotic Agents, volume 2466 of LNCS. Springer Verlag, 2002.
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•   D. Hähnel, D. Schulz, and W. Burgard.
Map Building with Mobile Robots in Populated Environments.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2002.
bib | .pdf ]
•   D. Schulz, M. Moors, W. Burgard, and A. Cremers.
A Statistical Approach to Tracking Multiple Moving People with a Mobile Robot and its Application to Improved Tele-Presence.
In Proc. of the VDI-Conference Robotik 2002 (Robotik), 2002.
bib ]
•   J. Wolf, W. Burgard, and H. Burkhardt.
Using an Image Retrieval System for Vision-based Mobile Robot Localization.
In Proc. of the International Conference on Image and Video Retrieval (CIVR), 2002.
bib | .pdf ]
•   J. Wolf, W. Burgard, and H. Burkhardt.
Robust Vision-based Localization for Mobile Robots using an Image Retrieval System Based on Invariant Features.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2002.
bib | .pdf ]
•   W. Burgard, P. Trahanias, D. Hähnel, M. Moors, D. Schulz, H. Baltzakis, and A. A..
TOURBOT and WebFAIR: Web-Operated Mobile Robots for Tele-Presence in Populated Exhibitions.
In Proc. of the IROS 02 Workshop on Robots in Exhibition, 2002.
bib | .pdf ]
•   D. Hähnel and W. Burgard.
Probabilistic Matching for 3D Scan Registration.
In Proc. of the VDI-Conference Robotik 2002 (Robotik), 2002.
bib | .pdf ]
•   C. Stachniss and W. Burgard.
An Integrated Approach to Goal-directed Obstacle Avoidance under Dynamic Constraints for Dynamic Environments.
In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pages 508--513, Lausanne, Switzerland, 2002.
bib | DOI | .pdf ]
•   C. Stachniss.
Zielgerichtete Kollisionsvermeidung für mobile Roboter in dynamischen Umgebungen. Master's thesis, University of Freiburg, Department of Computer Science, 2002. In German.
bib | .pdf ]

2001

•   M. Beetz, T. Arbuckle, T. Belker, M. Bennewitz, W. Burgard, A. B. Cremers, D. Fox, H. Grosskreutz, D. Hähnel, and D. Schulz.
Integrated Plan-based Control of Autonomous Service Robots in Human Environments.
IEEE Intelligent Systems, 16, 2001.
bib | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Exploiting Constraints During Prioritized Path Planning for Teams of Mobile Robots.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2001.
bib | DOI | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Constraint-based Optimization of Priority Schemes for Decoupled Path Planning Techniques.
In Proc. of the 24th German / 9th Austrian Conference on Artificial Intelligence. Springer Verlag, 2001.
bib | .pdf ]
•   M. Bennewitz, W. Burgard, and S. Thrun.
Optimizing Schedules for Prioritized Path Planning of Multi-Robot Systems.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2001.
bib | DOI | .pdf ]
•   M. Bennewitz and W. Burgard.
Finding Solvable Priority Schemes for Decoupled Path Planning Techniques for Teams of Mobile Robots.
In Proc. of the 9th International Symposium on Intelligent Robotic Systems (SIRS), 2001.
bib | .pdf ]
•   Y. Liu, R. Emery, D. Chakrabarti, W. Burgard, and S. Thrun.
Using EM to Learn 3D Models of Indoor Environments with Mobile Robots.
In Proc. of the International Conference on Machine Learning (ICML), 2001.
bib | .ps.gz ]
•   D. Schulz and W. Burgard.
Probabilistic State Estimation of Dynamic Objects with a Moving Mobile Robot.
Robotics and Autonomous Systems, 34(2-3):107--115, 2001.
bib | .pdf ]
•   W. Burgard and D. Schulz.
Robust Visualization for Web-based Control of Mobile Robots.
In K. Goldberg and R. Siegwart, editors, Robots on the Web: Physical Interaction through the Internet. MIT-Press, 2001.
bib | .ps.gz ]
•   D. Schulz, W. Burgard, D. Fox, and A. Cremers.
Tracking Multiple Moving Targets with a Mobile Robot using Particle Filters and Statistical Data Association.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2001.
bib | .ps.gz ]
•   D. Schulz, W. Burgard, D. Fox, and A. Cremers.
Tracking Multiple Moving Objects with a Mobile Robot.
In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2001.
bib | .pdf ]
•   S. Thrun, D. Fox, W. Burgard, and D. F..
Robust Monte-Carlo Localization for Mobile Robots.
Artificial Intelligence, 128(1-2):99--141, 2001.
bib | .pdf ]
•   D. Hähnel, W. Burgard, and S. Thrun.
Learning Compact 3D Models of Indoor and Outdoor Environments with a Mobile Robot.
In Proc. of the fourth European workshop on advanced mobile robots (EUROBOT), 2001.
bib ]

2000

•   S. Thrun, M. Beetz, M. Bennewitz, W. Burgard, A. B. Cremers, D. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, J. Schulte, and D. Schulz.
Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva.
International Journal of Robotics Research (IJRR), 19(11):972--999, 2000.
bib | .pdf ]
•   M. Bennewitz and W. Burgard.
An Experimental Comparison of Path Planning Techniques for Teams of Mobile Robots.
In Proc. of the Fachgespräche Autonome Mobile Systeme (AMS), 2000.
bib | .pdf ]
•   M. Bennewitz and W. Burgard.
Coordinating the Motions of Multiple Mobile Robots Using a Probabilistic Model.
In Proc. of the 8th International Symposium on Intelligent Robotic Systems (SIRS), 2000.
bib | .pdf ]
•   M. Bennewitz and W. Burgard.
A Probabilistic Method for Planning Collision- free Trajectories of Multiple Mobile Robots.
In Proc. of the Workshop “Service Robotics - Applications and Safety Issues in an Emerging Market” at the 14th European Conference on Artificial Intelligence (ECAI), 2000.
bib | .pdf ]
•   W. Burgard, M. Moors, D. Fox, R. Simmons, and S. Thrun.
Collaborative Multi-Robot Exploration.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2000.
bib | .ps.gz ]
•   W. Burgard, A. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun.
Experiences with an Interactive Museum Tour-Guide Robot.
Artificial Intelligence, 114(1-2):3--55, 2000.
bib | .ps.gz ]
•   D. Fox, W. Burgard, H. Kruppa, and S. Thrun.
Efficient multi-robot localization based on Monte Carlo approximation.
In J. Hollerbach and D. Koditschek, editors, Robotics Research: The Ninth International Symposium. Springer-Verlag, London, 2000.
bib | .ps.gz ]
•   D. Fox, S. Thrun, F. Dellaert, and W. Burgard.
Particle filters for mobile robot localization.
In A. Doucet, N. de Freitas, and N. Gordon, editors, Sequential Monte Carlo Methods in Practice. Springer Verlag, New York, 2000.
bib | .ps.gz ]
•   D. Fox, W. Burgard, H. Kruppa, and S. Thrun.
A Probabilistic Approach to Collaborative Multi-Robot Localization.
Autonomous Robots, 8(3), 2000.
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•   A. Knoll, W. Burgard, and T. Christaller.
Robotik.
In G. Görz, C.-R. Rollinger, and J. Schneeberger, editors, Handbuch der Künstlichen Intelligenz. Oldenbourg, 2000. In German.
bib ]
•   D. Schulz, W. Burgard, and A. Cremers.
State Estimation Techniques for 3D- Visualizations of Web-based Tele-operated Mobile Robots.
Proc. of the German Conference on Artificial Intelligence (KI), Germany, 4, 2000.
bib | .pdf ]
•   D. Schulz, W. Burgard, D. Fox, S. Thrun, and A. Cremers.
Web Interfaces for Mobile Robots in Public Places.
IEEE Robotics & Automation Magazine, 2000.
bib | .ps.gz ]
•   R. Simmons, D. Apfelbaum, W. Burgard, D. Fox, M. Moors, S. Thrun, and H. Younes.
Coordination for Multi-Robot Exploration and Mapping.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 2000.
bib | .ps.gz ]
•   S. Thrun, D. Fox, and W. Burgard.
Monte Carlo Localization with Mixture Proposal Distributions.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 2000.
bib | .ps.gz ]
•   S. Thrun, W. Burgard, and D. Fox.
A Real-Time Algorithm for Mobile Robot Mapping With Applications to Multi-Robot and 3D Mapping.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2000.
bib | .ps.gz ]

Before 2000

•   S. Thrun, M. Bennewitz, W. Burgard, A. Cremers, F. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz.
MINERVA: A Tour-Guide Robot that learns.
In Proc. of the the 23rd German Conference on Artificial Intelligence (KI). Springer Verlag, 1999.
bib | .pdf ]
•   S. Thrun, M. Bennewitz, W. Burgard, F. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz.
MINERVA: A Second-Generation Museum Tour-Guide Robot.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 1999.
bib | DOI | .pdf ]
•   S. Thrun, M. Bennewitz, W. Burgard, A. Cremers, F. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz.
Experiences with two Deployed Interactive Tour- guide Robots.
In Proc. of the International Conference on Field and Service Robotics (FSR), 1999.
bib | .pdf ]
•   W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun.
Sonar-Based Mapping of Large-Scale Mobile Robot Environments Using EM.
In Proc. of the International Conference on Machine Learning (ICML), 1999.
bib | .ps.gz ]
•   F. Dellaert, D. Fox, W. Burgard, and S. Thrun.
Monte Carlo Localization for Mobile Robots.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 1999.
bib | .ps.gz ]
•   F. Dellaert, W. Burgard, D. Fox, and S. Thrun.
Using the Condensation Algorithm for Robust, Vision-based Mobile Robot Localization.
In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 1999.
bib | .ps.gz ]
•   W. Burgard, U. Nehmzow, S. Vestli, and G. Schweizer, editors.
Proc. of the third European Workshop on Advanced Mobile Robots (EUROBOT), 1999.
bib ]
•   D. Fox, W. Burgard, H. Kruppa, and S. Thrun.
Collaborative Multi-Robot Localization.
In Proc. of the German Conference on Artificial Intelligence (KI), Germany. Springer Verlag, 1999.
bib | .ps.gz ]
•   D. Fox, W. Burgard, and S. Thrun.
Markov Localization for Reliable Robot Navigation and People Detection.
In Modelling and Planning for Sensor-Based Intelligent Robot Systems, LNCS. Springer Verlag, 1999.
bib | .ps.gz ]
•   D. Fox, W. Burgard, and S. Thrun.
Markov Localization for Mobile Robots in Dynamic Environments.
Journal of Artificial Intelligence Research (JAIR), 11:391--427, 1999.
bib | .ps.gz ]
•   D. Fox, W. Burgard, F. Dellaert, and S. Thrun.
Monte Carlo Localization: Efficient Position Estimation for Mobile Robots.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 1999.
bib | .ps.gz ]
•   D. Fox, W. Burgard, H. Kruppa, and S. Thrun.
A Monte Carlo Algorithm for Multi-Robot Localization.
Technical Report CMS-CS-99-120, Carnegie Mellon University, 1999.
bib | .ps.gz ]
•   D. Fox, W. Burgard, and S. Thrun.
Probabilistic Methods for Mobile Robot Mapping.
In Proc. of the IJCAI-99 Workshop on Adaptive Spatial Representations of Dynamic Environments, Stockholm, Sweden, 1999.
bib | .ps.gz ]
•   W. Burgard, T. Christaller, and A. Cremers, editors.
Proc. of the 22nd German Conference on Artificial Intelligence (KI), LNCS. Springer Verlag, 1999.
bib ]
•   N. Roy, W. Burgard, D. Fox, and S. Thrun.
Coastal Navigation: Mobile Robot Navigation with Uncertainty in Dynamic Environments.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 1999.
bib | .ps.gz ]
•   D. Schulz, W. Burgard, and A. Cremers.
Robust Visualization of Navigation Experiments with Mobile Robots over the Internet.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1999.
bib | .ps.gz ]
•   S. Thrun, J. Langford, and D. Fox.
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes.
In Proc. of the International Conference on Machine Learning (ICML), 1999.
bib | .ps.gz ]
•   M. Beetz, W. Burgard, D. Fox, and A. Cremers.
Integrating Active Localization into High-level Robot Control Systems.
Robotics and Autonomous Systems, 23:205--220, 1998.
bib | .ps.gz ]
•   W. Burgard, A. Derr, D. Fox, and A. Cremers.
Integrating global position estimation and position tracking for mobile robots: the Dynamic Markov Localization approach.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
bib | .ps.gz ]
•   W. Burgard, A. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun.
The Interactive Museum Tour-Guide Robot.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 1998.
bib | .ps.gz ]
•   W. Burgard, A. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun.
The Museum Tour-Guide Robot RHINO.
In Proc. of Fachgespräch Autonome Mobile Systeme (AMS'98), Karlsruhe, Germany, 1998.
bib ]
•   W. Burgard, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, S. Thrun, and A. Cremers.
Real Robots for the Real World --- The RHINO Museum Tour-guide Project.
In Proc. of the AAAI 1998 Spring Symposium on Integrating Robotics Research: Taking the Next Leap, 1998.
bib ]
•   W. Burgard, A. Cremers, D. Fox, D. Hähnel, A. Kappel, and S. Lüttringhaus-Kappel.
Verbesserte Brandfrüherkennung im Steinkohlenbergbau durch Vorhersage von CO-Konzentrationen.
In KI Themenheft Data Mining, volume 1. ScienTec Publishing GmbH, 1998. In German.
bib ]
•   D. Fox, W. Burgard, and S. Thrun.
Active Markov Localization for Mobile Robots.
Robotics and Autonomous Systems, 25:195--207, 1998.
bib | .ps.gz ]
•   D. Fox, W. Burgard, S. Thrun, and A. Cremers.
A Hybrid Collision Avoidance Method For Mobile Robots.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 1998.
bib | .ps.gz ]
•   D. Fox, W. Burgard, S. Thrun, and A. Cremers.
Position Estimation for Mobile Robots in Dynamic Environments.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 1998.
bib | .ps.gz ]
•   J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige.
An Experimental Comparison of Localization Methods.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
bib | .ps.gz ]
•   D. Hähnel, W. Burgard, and G. Lakemeyer.
GOLEX --- Bridging the Gap between Logic (GOLOG) and a Real Robot.
In Proc. of the 22nd German Conference on Artificial Intelligence (KI'98), LNCS, Bremen, Germany, 1998. Springer Verlag.
bib | .ps.gz ]
•   N. Roy, W. Burgard, D. Fox, and S. Thrun.
Coastal Navigation: Robot Motion with Uncertainty.
In Proc. of the 1998 AAAI Fall Symposium, 1998.
bib ]
•   F. Schönherr, J. Hertzberg, and W. Burgard.
Probabilistic Mapping of Unexpected Objects by a Mobile Robot.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
bib ]
•   S. Thrun, A. Bücken, W. Burgard, D. Fox, T. Fröhlinghaus, D. Hennig, T. Hofmann, M. Krell, and T. Schimdt.
Map Learning and High-Speed Navigation in RHINO.
In D. Kortenkamp, R. Bonasso, and R. Murphy, editors, Artificial Intelligence and MobileRobots. MIT/AAAI Press, Cambridge, MA, 1998.
bib | .ps.gz ]
•   S. Thrun, J.-S. Gutmann, D. Fox, W. Burgard, and B. Kuipers.
Integrating Topological and Metric Maps for Mobile Robot Navigation: A Statistical Approach.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 1998.
bib | .ps.gz ]
•   S. Thrun, D. Fox, and W. Burgard.
Probabilistic Mapping of an Environment by a Mobile Robot.
In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 1998.
bib | .ps.gz ]
•   S. Thrun, D. Fox, and W. Burgard.
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots.
Machine Learning, 31:29--53, 1998. Also appeared in Autonomous Robots 5, pp. 253--271, joint issue.
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•   A. Hopp, D. Schulz, W. Burgard, A. Cremers, and D. Fellner.
Virtual Reality Visualization of Distributed Tele-Experiments.
In IEEE Industrial Electronics Conference (IECON), 1998.
bib | .ps.gz ]
•   D. Fox, W. Burgard, and S. Thrun.
The Dynamic Window Approach to Collision Avoidance.
IEEE Robotics & Automation Magazine, 4(1), March 1997.
bib | .ps.gz ]
•   M. Beetz, W. Burgard, A. Cremers, and D. Fox.
Active Localization for Service Robot Applications.
In Proc. of the 5th Symposium for Intelligent Robotics Systems (SIRS'97), Stockholm, Sweden, 1997.
bib ]
•   W. Burgard, D. Fox, and S. Thrun.
Active Mobile Robot Localization.
In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), 1997.
bib | .ps.gz ]
•   W. Burgard, D. Fox, and D. Hennig.
Fast Grid-Based Position Tracking for Mobile Robots.
In Proc. of the German Conference on Artificial Intelligence (KI), Germany. Springer Verlag, 1997.
bib | .ps.gz ]
•   W. Burgard, A. B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun.
The RHINO museum tour-guide project. http://www.iai.uni- bonn.de/~rhino/tourguide, 1997.
bib ]
•   W. Burgard, D. Fox, and S. Thrun.
Active Mobile Robot Localization by Entropy Minimization.
In Proc. of the Second Euromicro Workshop on Advanced Mobile Robots. IEEE Computer Society Press, 1997.
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•   S. Thrun, D. Fox, and W. Burgard.
Probabilistic State Estimation in Robotics.
In Proc. of the Workshop on Self-Organization of Adaptive Behavior, Ilmenau, Germany. VDI-Verlag, 1997.
bib | .ps.gz ]
•   W. Burgard, D. Fox, D. Hennig, and T. Schmidt.
Estimating the Absolute Position of a Mobile Robot Using Position Probability Grids.
In Proc. of the National Conference on Artificial Intelligence (AAAI), 1996.
bib | .pdf ]
•   W. Burgard, A. Cremers, D. Fox, M. Heidelbach, A. Kappel, and S. Lüttringhaus Kappel.
Knowledge-enhanced CO-monitoring in Coal Mines.
In Proc. of the Ninth International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems, 1996.
bib | .ps.gz ]
•   W. Burgard, A. Cremers, D. Fox, M. Heidelbach, A. Kappel, and S. Lüttringhaus-Kappel.
Logic Programming Tools Applied to Fire Detection in Hard-coal Mines.
In Proc. of the Joint International Conference and Symposium on Logic Programming, 1996.
bib ]
•   W. Burgard, D. Fox, D. Hennig, and T. Schmidt.
Position Tracking with Position Probability Grids.
In Proc. of the First Euromicro Workshop on Advanced Mobile Robots. IEEE Computer Society Press, 1996.
bib | .ps.gz ]
•   D. Fox, W. Burgard, and S. Thrun.
Controlling Synchro-drive Robots with the Dynamic Window Approach to Collision Avoidance.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1996.
bib | .ps.gz ]
•   W. Burgard, A. Cremers, T. Kolbe, and L. Plümer.
Object construction by deduction for a 3D geo- information system of a mine.
In Proceedings of the 4th Int. Conf. on Practical Application of Prolog (PAP), 1996.
bib ]
•  
Proc. of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT'96). IEEE Computer Society Press, 1996.
bib ]
•   J. Buhmann, W. Burgard, A. Cremers, D. Fox, T. Hofmann, F. Schneider, J. Strikos, and S. Thrun.
The Mobile Robot Rhino.
AI Magazine, 16(2):31--38, 1995.
bib | .ps.gz ]
•   W. Burgard.
Goal-directed forward chaining: A tuple- oriented bottom-up approach.
In C. Beierle and L. Plümer, editors, Logic Programming: Formal Methods and Practical Applications. Elsevier Science B.V., 1995.
bib ]
•   W. Burgard.
Goal-directed Forward Chaining for Logic Programs.
PhD thesis, University of Bonn, Department of Computer Science, 1991.
bib | .pdf ]
•   W. Burgard.
Efficiency Considerations on Goal-Directed Forward Chaining for Logic Programs.
In Proceedings of the 4th workshop on Computer Science Logic (CSL), 1990.
bib ]
•   W. Burgard.
PROSPERT: An Expert System for the Syntesis of Chemical Processes. Master's thesis, University of Dortmund, Department of Computer Science, 1987. In German.
bib ]
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