The following is a very tentative schedule.
Lecture | Topic |
1 | Introduction, Project I discussion and assignment, Lie groups |
2-3 | Lie groups (cont.), geometry, 3-D kinematics |
4 | Simulation and experiment design, overview of resources, control of nonholonomic robots with examples |
5 | Simulation environments and engines, introduction to Stage/Gazebo. |
6-7 | Continuous feedback laws, navigation functions, geometric control |
8 | Geometric control (cont.) with examples using an aerial robot |
9-13 | Motion Planning |
14 | Motion planning in two and three dimensions with examples |
15 | Project I presentations, project II discussion and assignment |
16 | Introduction to filtering and estimation, the Kalman filter |
17 | Parametric filtering: Kalman filter, information form of Kalman filter, extended Kalman filter, unscented Kalman filter with examples |
18-19 | Case study: A tracking system for indoor localization. Sensor models and considerations.
Pragmatics of using odometry, laser, and camera data. |
20 | Non-parametric filtering and particle filters with examples |
21-22 | Simultaneous localization and mapping, EKF SLAM and FastSLAM with examples |
23-24 | Sampling based motion planning |
25 | A*-based time-constrained planning |
26 | planning in dynamic environments |
27-28 | Distributed robotics, multi-agent formation control and manipulation |
29 | planning under uncertainty |
30 | learning to plan and control |
31-32 | Project presentations |