6 EC
Semester 1, period 1
5204PRRO6Y
| Owner | Master Artificial Intelligence |
| Coordinator | dr. Arnoud Visser |
| Part of | Master Artificial Intelligence, year 2 |
Probabilistic robotics is a subfield of robotics concerned with the perception and control part. It relies on statistical techniques for representing information and making decisions. By doing so, it accommodates the uncertainty that arises in most contemporary robotics applications.
This course is based on the book 'Probabilistic Robotics', from Sebastian Thrun, Wolfram Burgard and Dieter Fox. The book concentrates on the algorithms, and only offers a limited number of exercises. Their suggestion is to accompany the book with a number of practical, hands-on assignments for each chapter. The assignments of this course are designed to understand the basic problems concerning mobile robotics.
Sebastian Thrun, Wolfram Burgard and Dieter Fox, Probabilistic Robotics, The MIT Press, 2005. ISBN: 9780262201629, 3rd edition.
Matlab, Python
At the end of the course, the student is able to:
The lectures are to understand the mathematical foundations of the algorithms, the computer lab session are intended to translate the algorithms to software to control robots in the real-world.
|
Activity |
Number of hours |
|
Lectures |
24 |
|
Lab sessions |
24 |
|
Self study |
120 |
The programme does not have requirements concerning attendance (OER-B).
| Item and weight | Details |
|
Final grade | |
|
1 (50%) Exam | |
|
1 (50%) Practical assignments | |
|
0.25 (11%) Exercise 2.8.4 | |
|
0.25 (11%) Exercise 4.6.1 & 4.6.4 | |
|
0.25 (11%) Exercise 5.8.4 & 5.8.5 and Odometry model | |
|
0.5 (22%) Kalman localization and SLAM | |
|
1 (44%) Particle SLAM on a Nao field |
Feedback on the assignments will be directly given on the reports uploaded to Blackboard.
The final exam can be inspected at the coordinator's office (C3.157),
individual assignment
individual assignment
individual assignment
pair assignment
groups assignment
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.uva.nl/plagiarism
| Week | Chapters | Assignment | Deadline |
| 1 | 1 & 2 | Exercise 2.8.4 | 07/09/2017 13:00 |
| 2 | 3 & 4 | Exercise 4.6.1 & 4.6.4 | 19/09/2017 13:00 |
| 3 | 5 - 8 | Exercise 5.8.4 & 5.8.5 and Odometry model | 26/09/2017 13:00 |
| 4 | 9 & 10 | Kalman localization and SLAM | |
| 5 | 11 & 12 | 10/10/2017 13:00 | |
| 6 | 13 & 14 | Particle SLAM on a Nao field | |
| 7 | 17 | 22/10/2017 23:59 |
The schedule for this course is published on DataNose.