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Introduction to Mobile Robotics - SS 2015

Introduction to Mobile Robotics (engl.) - Autonomous Mobile Systems

This course will introduce basic concepts and techniques used within the field of mobile robotics. We analyze the fundamental challenges for autonomous intelligent systems and present the state of the art solutions. Among other topics, we will discuss:
  • Kinematics,
  • Sensors,
  • Vehicle localization,
  • Map building,
  • SLAM,
  • Path planning,
  • Exploration of unknown terrain

Lectures

Lecture Dates Topic Slides Recordings
00 22-04-2015 Introduction PDF MP4
01 24-04-2015 Linear Algebra PDF MP4
02 29-04-2015 Robot Control Paradigms PDF MP4
03 29-04-2015 Wheeled Locomotion PDF MP4
04 06-05-2015 Proximity Sensors PDF MP4
05 06-05-2015
08-05-2015
13-05-2015		 Probabilistic Robotics PDF MP4
MP4
MP4
06 15-05-2015
20-05-2015		 Probabilistic Motion Models PDF MP4
MP4
07 20-05-2015
22-05-2015 		Probabilistic Sensor Models PDF MP4
MP4
08 03-06-2015 Bayes Filter - Discrete Filters PDF MP4
09 03-06-2015
05-06-2015 		Bayes Filter - Particle Filter and MCL PDF MP4
MP4
10 10-06-2015 Bayes Filter - Kalman Filter PDF MP4
11 10-06-2015 Bayes Filter - Extended Kalman Filter PDF MP4
12 12-06-2015
17-06-2015 		Grid Maps and Mapping With Known Poses PDF MP4
MP4
13 17-06-2015 SLAM - Simultaneous Localization and Mapping PDF MP4
14 19-06-2015 SLAM - Landmark-based FastSLAM PDF MP4
15 24-06-2015 SLAM - Grid-based FastSLAM PDF MP4
16 26-06-2015 SLAM - Graph-based SLAM PDF MP4
17 01-07-2015 Techniques for 3D Mapping PDF MP4
18 01-07-2015
03-07-2015 		Iterative Closest Point Algorithm PDF MP4
MP4
19 03-07-2015
08-07-2015
10-07-2015 		Path and Motion Planning PDF MP4
MP4
MP4
20 15-07-2015 Multi-Robot Exploration PDF MP4
21 15-07-2015
17-07-2015 		Information Driven Exploration PDF MP4
22 22-07-2015 Summary PDF

Exercises

Solving and submitting the exercise sheets is recommended but not mandatory to be admitted to the final exam. There are no bonus points.

The exercises should be solved in groups of two students. Submit a single tar/zip file with all codes, scripts and a single pdf with all answers (programs and figures).

In general, assignments will be published on Friday and have to be submitted the following Thursday before midnight. Submit programming exercises via email to mobilerobotics@informatik.uni-freiburg.de

During the exercise class the solutions will be discussed. Decide if you prefer to use Octave or Python and join the corresponding exercise group. Please adhere to your initial choice.

Octave: Group 1 - Room: SR 01-009/13 - Organized by: Ayush Dewan, Martina Deturres
Python: Group 2 - Room: HS 00 026 µ - Organized by: Tayyab Naseer, Tim Caselitz

Join this forum for discussing questions on exercises and lectures
https://groups.google.com/forum/#!forum/ais_introtorobotics15

Sheet Deadline Topic Octave Python Download
01 30-04-2015 Setup Octave / Python PDF PDF
02 07-05-2015 Linear Algebra, Locomotion, Sensing PDF PDF laserscan.dat
03 14-05-2015 Locomotion, Bayes Rule PDF PDF
04 28-05-2015 Sampling, Motion Models PDF PDF
05 11-06-2015 Sensor Models PDF PDF
06 18-06-2015 Discrete Filter, Particle Filter PDF PDF pf_framework_octave.tar.gz
pf_framework_python.tar.gz
07 25-06-2015 Extended Kalman Filter PDF PDF ekf_framework_octave.tar.gz
ekf_framework_python.tar.gz
08 02-07-2015 Mapping with Known Poses PDF PDF
09 09-07-2015 Simultaneous Localization and Mapping PDF PDF
10 16-07-2015 FastSLAM PDF PDF fastslam_framework_octave.tar.gz
fastslam_framework_python.tar.gz
11 23-07-2015 Iterative Closest Point Algorithm and Recapitulation PDF PDF icp_framework_octave.tar.gz
icp_framework_python.tar.gz

Additional Material

  • Notes on one dimensional Gaussians (PDF)
  • Notes on multi dimensional Gaussians (PDF)
  • Octave cheat sheet (PDF)
  • Python cheat sheet (PDF)
  • Matrix cookbook (PDF)
Benutzerspezifische Werkzeuge