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Introduction to Mobile Robotics - SS 2018

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

  • Lecturer: Prof. Dr. Wolfram Burgard,
  • Co-organizers: Chau Do Marina Kollmitz, Lukas Luft
  • Lecture: Wed 16.00-18.00 / Fri 14.00-15.00, Building: 101, Room: SR 00-010/014
  • Exercises: Fri 15.00-16.00, Building: 101, Room: SR 00-010/014
  • Exam: The exam is ORAL for bachelor students of Embedded Systems Engineering and WRITTEN for everyone else.
    1. WRITTEN: Wed 19-09-2018, 10:00, Room: TBA
    2. ORAL: TBA


Lecture Dates Topic Slides Recordings
00 18-04-2018 Introduction PDF MP4
01 20-04-2018
Linear Algebra PDF MP4
02 25-04-2018 Robot Control Paradigms PDF MP4
03 25-04-2018
Wheeled Locomotion PDF MP4
04 27-04-2018 Proximity Sensors PDF MP4
05 02-05-2018
Probabilistic Robotics PDF MP4
06 09-05-2018
Probabilistic Motion Models PDF MP4
07 11-05-2018 Probabilistic Sensor Models PDF MP4
08 18-05-2018 Bayes Filter - Discrete Filters PDF MP4
09 30-05-2018
Bayes Filter - Particle Filter and MCL PDF MP4
10 06-06-2018 Bayes Filter - Kalman Filter PDF MP4
11 08-06-2018 Bayes Filter - Extended Kalman Filter PDF MP4
12 13-06-2018
Grid Maps and Mapping With Known Poses PDF MP4
13 22-06-2018 SLAM - Simultaneous Localization and Mapping PDF MP4


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

Exercise sheets will be published on Fridays and will be discussed in class one week later. We strongly encourage you to solve the exercise sheets beforehand to benefit from the discussions in class.

Join this Google group forum for discussing questions on lectures and exercises or send a mail to mobilerobotics@informatik.uni-freiburg.de for an appointment with one of the teaching assistants.

Sheet Due date Topic Exercise Sheet Exercise Material Solutions
01 20-04-2018 Setup Python PDF func.py
02 27-04-2018 Linear Algebra PDF laserscan.dat PDF
03 04-05-2018 Locomotion, Differential Drive PDF PDF
04 11-05-2018 Bayes Rule PDF PDF
05 18-05-2018 Sampling, Motion Models PDF PDF
06 01-06-2018 Sensor Models PDF PDF
07 08-06-2018 Discrete Filter, Particle Filter PDF pf_framework.tar.gz PDF
08 15-06-2018 Extended Kalman Filter PDF kf_framework.tar.gz PDF
09 22-06-2018 Mapping with Known Poses PDF PDF
10 29-06-2018 Simultaneous Localization and Mapping PDF

Additional Material

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