Lecture Slides
1 – Introduction
2 – Background – Linear Systems
2 – Background – Probability
2 – Background – Optimization
2 – Background – Coordinate Systems
3 – Motion Modeling
4 – Measurement Modeling
5 – Estimation – Bayes, Kalman
5 – Estimation – Particle
6 – Mapping – Localization and Mapping
6 – Mapping – SLAM
6 – Mapping – GraphSLAM
7 – Control
8 – Planning – Reactive, Graph-based
8 – Planning – Sampling-based
8 – Planning – Optimal
9 – Quadrotors
10 – Review
All slides in one .zip archive |
Lecture Videos
1 – Introduction
2 – Background 1
2 – Background 2
2 – Background 3, Motion 1
3 – Motion 2, Measurement 1
4 – Measurement 2
4 – Measurement 3, Estimation 1
5 – Estimation 2
5 – Estimation 3
5 – Estimation 4
5 – Estimation 5, Mapping 1
6 – Mapping 2
6 – Mapping 3
6 – Mapping 4
7 – Controls 1
7 – Controls 2
8 – Planning 1
8 – Planning 2
8 – Planning 3
8 – Planning 4
8 – Planning 5, Quadrotors 1
9 – Quadrotors 2
10 – Review 1
10 – Review 2 |
