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, Daniel Büscher, Lukas Luft
- Co-organizers: Chau Do Marina Kollmitz,
- 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 Computer Science and WRITTEN for everyone else.
- WRITTEN: Wed 19-09-2018, 10:00, Building: 082 Room: 00-006 (Kinohörsaal)
- ORAL: Please check the date in your HISinOne
- post-exam review: Tue 23-10-2018, 10:00-12:00, Building: 101, Room: SR 01-016
- (retake) exam ws18/19: oral, individual time slots in March 2019. Check HISinOne
- exam question round: Mondays, 18-02-2019 - 04-03-2019, 14:20-15:00, Building 080 upstairs meeting room
Lectures
| Lecture | Dates | Topic | Slides | Recordings |
| 00 | 18-04-2018 | Introduction | MP4 | |
| 01 | 20-04-2018 25-04-2018 |
Linear Algebra | MP4
MP4 |
|
| 02 | 25-04-2018 | Robot Control Paradigms | MP4 | |
| 03 | 25-04-2018
27-04-2018 |
Wheeled Locomotion | MP4
MP4 |
|
| 04 | 27-04-2018 | Proximity Sensors | MP4 | |
| 05 | 02-05-2018 02-05-2018 04-05-2018 |
Probabilistic Robotics | MP4
MP4 MP4 |
|
| 06 | 09-05-2018 09-05-2018 |
Probabilistic Motion Models | MP4
MP4 |
|
| 07 | 11-05-2018 | Probabilistic Sensor Models | MP4
MP4 |
|
| 08 | 18-05-2018 | Bayes Filter - Discrete Filters | MP4 | |
| 09 | 30-05-2018 01-06-2018 | Bayes Filter - Particle Filter and MCL | MP4
MP4 |
|
| 10 | 06-06-2018 | Bayes Filter - Kalman Filter | MP4 | |
| 11 | 08-06-2018 | Bayes Filter - Extended Kalman Filter | MP4 | |
| 12 | 13-06-2018 15-06-2018 |
Grid Maps and Mapping With Known Poses | MP4
MP4 | |
| 13 | 22-06-2018 | SLAM - Simultaneous Localization and Mapping | MP4 | |
| 14 | 27-06-2018 | SLAM - Landmark-based FastSLAM | MP4 | |
| 15 | 29-06-2018 04-07-2018 |
SLAM - Grid-based FastSLAM | MP4 MP4 |
|
| 16 | 04-07-2018 06-07-2018 |
SLAM - Graph-based SLAM | MP4 MP4 |
|
| 17 | 11-07-2018 | Techniques for 3D Mapping | MP4 | |
| 18 | 11-07-2018 | Iterative Closest Point Algorithm | MP4_ss16 |
|
| 19 | 13-07-2018 18-07-2018 18-07-2018 |
Path and Motion Planning | MP4_ss16
MP4 MP4 |
|
| 20 | 20-07-2018 | Multi-Robot Exploration | MP4 MP4_ss16 |
|
| 21 | 20-07-2018 | 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.
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 | |
Setup Python | func.py | ||
| 02 | |
Linear Algebra | laserscan.dat | ||
| 03 | |
Locomotion, Differential Drive | |||
| 04 | |
Bayes Rule | |||
| 05 | |
Sampling, Motion Models | |||
| 06 | |
Sensor Models | |||
| 07 | |
Discrete Filter, Particle Filter | pf_framework.tar.gz | ||
| 08 | |
Extended Kalman Filter | kf_framework.tar.gz | ||
| 09 | |
Mapping with Known Poses | |||
| 10 | |
Simultaneous Localization and Mapping | |||
| 11 | |
FastSLAM | fastSLAM_framework.tar.gz fastSLAM_algorithm.pdf |
||
| 12 | |
Iterative Closest Point Algorithm | icp_framework.tar.gz | ||
| 13 | |
Path Planning | planning_framework.tar.gz |