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.
- WRITTEN: Tue 06-10-2020, 9:30 - 11:30, Location: Building 082, Room 00-006 (Kinohörsaal)
- ORAL: Thu 08-10-2020, Time and Location TBA.
Lectures
| Lecture | Dates | Topic | Slides | Recordings |
| 00 | 13-05-2020 | Introduction | MP4 | |
| 01 | 20-05-2020 | Linear Algebra | MP4
MP4 |
|
| 02 | 27-05-2020 | Robot Control Paradigms | MP4 | |
| 03 | 27-05-2020 | Wheeled Locomotion | MP4
MP4 |
|
| 04 | 27-05-2020 | Proximity Sensors | MP4 | |
| 05 | 03-06-2020 | Probabilistic Robotics | MP4
MP4 MP4 |
|
| 06 | 10-06-2020 | Probabilistic Motion Models | MP4
MP4 |
|
| 07 | 17-06-2020 | Probabilistic Sensor Models | MP4
MP4 |
|
| 08 | 24-06-2020 | Bayes Filter - Discrete Filters | MP4 | |
| 09 | 24-06-2020 24-06-2020 | Bayes Filter - Particle Filter and MCL | MP4
MP4 |
|
| 10 | 01-07-2020 | Bayes Filter - Kalman Filter | MP4 | |
| 11 | 01-07-2020 | Bayes Filter - Extended Kalman Filter | MP4 | |
| 12 | 09-07-2020 | Grid Maps and Mapping With Known Poses | MP4
MP4 | |
| 13 | 15-07-2020 | SLAM - Simultaneous Localization and Mapping | MP4 | |
| 14 | 15-07-2020 | SLAM - Landmark-based FastSLAM | MP4 | |
| 15 | 15-07-2020 | SLAM - Grid-based FastSLAM | MP4 MP4 |
|
| 16 | 15-07-2020 | SLAM - Graph-based SLAM | MP4 MP4 |
|
| 17 | 22-07-2020 | Techniques for 3D Mapping | MP4 | |
| 18 | 22-07-2020 | Iterative Closest Point Algorithm | MP4 |
|
| 19 | 30-07-2020 | Path and Motion Planning | MP4
MP4 MP4 |
|
| 20 | 31-07-2020 | Multi-Robot Exploration | MP4 MP4 |
|
| 21 | 31-07-2020 | Information Driven Exploration | MP4 | |
| 22 | 31-07-2020 | Summary | MP4 |
Exercises
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 | |
Setup Python | func.py | ||
| 01 | |
Linear Algebra | laserscan.dat | ||
| 02 | |
Locomotion, Differential Drive | |||
| 03 | |
Bayes Rule | |||
| 04 | |
Sampling, Motion Models | |||
| 05 | |
Sensor Models | |||
| 06 | |
Discrete Filter, Particle Filter | pf_framework.tar.gz | ||
| 07 | |
Extended Kalman Filter | kf_framework.tar.gz | ||
| 08 | |
Mapping with Known Poses | |||
| 09 | |
FastSLAM | fastSLAM_framework.tar.gz fastSLAM_algorithm.pdf |
||
| 10 | |
Iterative Closest Point Algorithm | icp_framework.tar.gz | ||
| 11 | |
Path Planning | planning_framework.tar.gz |