Syllabus
- A reminder of probability theory
- Kalman filters and their variants
- Particle filters
- Probabilistic localization and mapping
- Decisioning and planning under uncertainty
Annotation
During its life a robot deals with many problems: It wakes up - without knowing where it is. It is going - without knowing how and where.
It is doing - without knowing what and why. These difficulties come from an inaccuracy of sensors and from a complexity of the real world, which cannot be accurately captured by a simple model.
Our goal for this class is to familiarize ourselves with various algorithmic methods, which help us with dealing with the uncertainty originating from our and robot's ignorance.