Contents

1. Introduction to Mobile Robotics
2. Basics of Probability Theory
3. State Estimation
4. Mapping
5. Markov Localization
6. Monte Carlo Localization
7. Simultaneous Localization and Mapping (SLAM)
8. Markov Decision Processes (MDPs)
9. Partially observable Markov Decision Processes (POMDPs)
10. Reasoning about action under uncertainty

Course Dates

The lecture starts on Friday, April 24, 2020.

Literature

S. Thrun, W. Burgard, and D. Fox, Probabilistic robotics. MIT Press, 2005.

RWTHMoodle

You can find further information in the RWTHMoodle Course Room.

Questions?

Please contact Till Hofmann for further questions.