Introduction to Mobile Robotics - SS 2019
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, Iman Nematollahi,
- Lecture: Wed 14.00-16.00 / Fri 16.00-17.00, Building: 101, Room: HS 00-036 (Schicksaal)
- Exercises: Fri 17.00-18.00, Building: 101, Room: SR 00-010/014
- Q&A session: Wed, August 28, 14.00-16.00, Building: 101, Room: HS 00-036 (Schicksaal)
- For questions,discussions regarding the lectures/tutorials an ILIAS forum is available: ILIAS Forum
- Exam: The exam is ORAL for bachelor students of Computer Science (except Prüfungsordnung 2018) and WRITTEN for everyone else.
- WRITTEN: Mon 02-09-2019, 14:00 - 16:00, Building: G.-Köhler-Allee 101, Room: 00-010/014
- ORAL: TBA
- Post-exam review: Thu 17-10-2019 and Thu 24-10-2019, 10:00-11:00, Building: 080, Room: Seminar room ground floor
Lectures
| Lecture | Dates | Topic | Slides | Recordings |
| 00 | 24-04-2019 | Introduction | MP4 | |
| 01 | 24-04-2019 26-04-2019 |
Linear Algebra | MP4
MP4 |
02 | 26-04-2019 | Robot Control Paradigms | MP4 |
| 03 | 03-05-2019 | Wheeled Locomotion | MP4
MP4 |
|
| 04 | 08-05-2019 | Proximity Sensors | MP4 | |
| 05 | 08-05-2019 10-05-2019 15-05-2019 |
Probabilistic Robotics | MP4
MP4 MP4 |
|
| 06 | 17-05-2019 22-05-2019 |
Probabilistic Motion Models | MP4
MP4 |
|
| 07 | 22-05-2019 24-05-2019 |
Probabilistic Sensor Models | MP4
MP4 |
|
| 08 | 29-05-2018 | Bayes Filter - Discrete Filters | MP4 | |
| 09 | 31-05-2019 05-06-2019 | Bayes Filter - Particle Filter and MCL | MP4
MP4 |
|
| 10 | 07-06-2019 | Bayes Filter - Kalman Filter | MP4 | |
| 11 | 19-06-2019 | Bayes Filter - Extended Kalman Filter | MP4 | |
| 12 | 21-06-2019 26-06-2018 |
Grid Maps and Mapping With Known Poses | MP4
MP4 | |
| 13 | 28-06-2019 | SLAM - Simultaneous Localization and Mapping | MP4 | |
| 14 | 03-07-2019 | SLAM - Landmark-based FastSLAM | MP4 | |
| 15 | 05-07-2019 10-07-2019 |
SLAM - Grid-based FastSLAM | MP4 MP4 |
|
| 16 | 10-07-2019 | SLAM - Graph-based SLAM | MP4 MP4 |
|
| 17 | 12-07-2019 | Techniques for 3D Mapping | MP4 | |
| 18 | 17-07-2019 | Iterative Closest Point Algorithm | MP4_ss16 |
|
| 19 | 17-07-2019 19-07-2019 |
Path and Motion Planning | MP4_ss16
MP4 MP4 |
|
| 20 | 24-07-2019 | Multi-Robot Exploration | MP4_ss16 | |
| 21 | 24-07-2019 | Information Driven Exploration | MP4_ss16 |
Exercises
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.
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 |
| 00 | |
Setup Python | |||
| 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 | |
Simultaneous Localization and Mapping | |||
| 10 | |
FastSLAM | fastSLAM_framework.tar.gz fastSLAM_algorithm.pdf |
||
| 11 | |
Iterative Closest Point Algorithm | icp_framework.tar.gz | ||
| 12 | |
Path Planning | planning_framework.tar.gz |