Summer 2024
Many confuse the recordings with actual lectures per week. The online
courses are from previous years and they have the advantage that you can stop the lecture at any time an
restart it at any slide later chosing it from the slide listing that can
be displayed on the left of the recording. I will repeat the outline of
the course here, so you can check how is our progress in the course of
the semester.
I give you some material ahead of time. You should finish processing the
corresponding videos when the corresponding homework set (see below)
gets presented.
Syllabus:
Section
Topic
Video # in Recordings
Homework
Representation:
How to represent the robot to simplify the planning task -
configuration space. Ways to reduce the robot to a point.
Video - 1.
HmSet 1
Direct Planning Methods
Planning of the complete path online - Bug algorithms
Video - 2.
HmSet 2
Planning of the complete path online - Wavefront planner
Video - 2.
HmSet 2
Planning Strategies
Complete Map Knowledge - Offline construction of roadmaps
Visibility Graph
Video - 2
HmSet 1
Complete Map Knowledge - Offline construction of roadmaps
Voronoi Graph
Video - 2
HmSet 1
Complete Map Knowledge - Offline construction of roadmaps
Trapezoidal Cell Decomposition and Boustraphedon
Video - 2
HmSet 2,3
Partial Map Knowledge (limited sensing) - Heuristic
Method based on Potential Field
Video - 3
HmSet 2,3
No Map Knowledge - Sampling-Based method
Multple Query Probabilistic Roadmap
Video - 4
HmSet 3
No Map Knowledge - Sampling-Based method
Single Query Probabilistic Roadmap
Video - 5
HmSet 3
Analysis of the Expansiveness (connectivity) of a graph
Video - 6
HmSet 3
Parametrization of the PRM (number of nodes etc) based on Expansiveness
Video - 6
HmSet 3
No Map Knowledge - Improvements of Sampling-Based
methods Obstacle-Based PRM, RRT
Video - 7
Expansiveness of the Space (PRM parametrization)
Methods to improve connectivity of probabilistic roadmaps
Video - 7
Fusion of Uncertain Data for Mapping
Gaussian Uncertainty, Linear Systems Fusion with Kalman Filter
Gaussian Uncertainty, non-Linear Systems Fusion with Extended Kalman Filter
Gaussian Uncertainty, highly non-Linear Systems Fusion with Uncented Kalman Filter
Arbitrary Uncertaintys Fusion with Bayesian and Particle Filter
Simultaneous Localization and Mapping (SLAM)