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Introduction to Mobile Robotics - SS 2020

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

  • Lecturer: Dr. Daniel Büscher, Lukas Luft
  • Co-organizers: Marina Kollmitz
  • Introduction session: There will be an intro lecture on May 13th, 12:00 via Zoom.
  • The first Q&A-Session / Exercise will take place on May 14th, 13:00 via Zoom.
  • Lecture: No on-site lectures will be provided this term. Please work over the lecture recordings (see below) in your own time.
  • Exercises: Thu (or Wed, see below) from 13:00 to 14:00, via Zoom. No recordings will be provided.
  • Q&A session: Fri, October 2, 10:00-11:00, via Zoom. Link announced in ILIAS.
  • Zoom meeting links will be announced in the ILIAS forum (see below). Please download and test the Zoom client before the intro session: zoom.us/download
  • For questions and discussions regarding the lectures/tutorials an ILIAS Forum is available. For access you might need to register to the ILIAS Course first.
  • Exam: The exam is WRITTEN for most students, except for bachelor students of computer science with Prüfungsordnung 2012.
    1. WRITTEN: Tue 06-10-2020, 9:30 - 11:30, Location: Building 082, Room 00-006 (Kinohörsaal)
    2. ORAL: Thu 08-10-2020, Time and Location TBA.


Lecture Dates Topic Slides Recordings
00 13-05-2020 Introduction PDF MP4
01 20-05-2020 Linear Algebra PDF MP4
02 27-05-2020 Robot Control Paradigms PDF MP4
03 27-05-2020 Wheeled Locomotion PDF MP4
04 27-05-2020 Proximity Sensors PDF MP4
05 03-06-2020 Probabilistic Robotics PDF MP4
06 10-06-2020 Probabilistic Motion Models PDF MP4
07 17-06-2020 Probabilistic Sensor Models PDF MP4
08 24-06-2020 Bayes Filter - Discrete Filters PDF MP4
09 24-06-2020
Bayes Filter - Particle Filter and MCL PDF MP4
10 01-07-2020 Bayes Filter - Kalman Filter PDF MP4
11 01-07-2020 Bayes Filter - Extended Kalman Filter PDF MP4
12 09-07-2020 Grid Maps and Mapping With Known Poses PDF MP4
13 15-07-2020 SLAM - Simultaneous Localization and Mapping PDF MP4
14 15-07-2020 SLAM - Landmark-based FastSLAM PDF MP4
15 15-07-2020 SLAM - Grid-based FastSLAM PDF MP4
16 15-07-2020 SLAM - Graph-based SLAM PDF MP4
17 22-07-2020 Techniques for 3D Mapping PDF MP4
18 22-07-2020 Iterative Closest Point Algorithm PDF MP4
19 30-07-2020 Path and Motion Planning PDF MP4
20 31-07-2020 Multi-Robot Exploration PDF MP4
21 31-07-2020 Information Driven Exploration PDF MP4
22 31-07-2020 Summary PDF MP4


Each exercise session consists of three parts: a short recap of the lecture, a Q&A session and the discussion of the exercise sheets. Please post your questions for the Q&A session at least 24h before the exercise session in the ILIAS forum.

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 about one week before the discussion session. We strongly encourage you to solve the exercise sheets beforehand to benefit from the discussions in class.

Send a mail to mobilerobotics@informatik.uni-freiburg.de for an appointment with one of the teaching assistants.

Sheet Discussion Topic Exercise Sheet Exercise Material Solutions
00 14-05-2020 (Thu) Setup Python PDF func.py
01 20-05-2020 (Wed) Linear Algebra PDF laserscan.dat PDF
02 28-05-2020 (Thu) Locomotion, Differential Drive PDF PDF
03 04-06-2020 (Thu) Bayes Rule PDF PDF
04 10-06-2020 (Wed) Sampling, Motion Models PDF PDF
05 18-06-2020 (Thu) Sensor Models PDF PDF
06 25-06-2020 (Thu) Discrete Filter, Particle Filter PDF pf_framework.tar.gz PDF
07 02-07-2020 (Thu) Extended Kalman Filter PDF kf_framework.tar.gz PDF
08 09-07-2020 (Thu) Mapping with Known Poses PDF PDF
09 16-07-2020 (Thu) FastSLAM PDF fastSLAM_framework.tar.gz
10 23-07-2020 (Thu) Iterative Closest Point Algorithm PDF icp_framework.tar.gz PDF
11 30-07-2020 (Thu) Path Planning PDF planning_framework.tar.gz PDF

Additional Material

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