Most readings will be distributed in class
| Week | Date | Content | Readings (book chapters) | Assignments | |
| Introduction and Paradigms | |||||
| #1 | January 4 | Introduction | |||
| January 6 | Robot control paradigms, Wheeled locomotion | ||||
| Probabilistic Models / State Estimation | |||||
| #2 | January 11 | Probabilities, Bayes rule, Bayes filters | 1, 2 | ||
| January 13 | Motion models, Sensor models | 5 | Project 1: Particle and Kalman filter localization | ||
| #3 | January 18 | Sensor models; Kalman filter | 6, 3.1-3.2 | ||
| Localization / Mapping / Tracking | |||||
| #3 | January 20 | EKF, UKF and localization (slides linked to previous lecture) | 3.3, 7.1-7.5 | ||
| #4 | January 25 | NO CLASS | |||
| January 27 | Particle filters and localization | 4, 8 | |||
| #5 | February 1 | Project 1 Demo | Project 1 Due; Project 2 | ||
| February 3 | Applications of particle filters | Ball tracking | |||
| #6 | February 8 | Map building: Occupancy grid maps | 9 | ||
| February 10 | Map building: SLAM | 10, 11 | |||
| #7 | February 15 | Map building: Fast-SLAM | |||
| February 17 | Map building: Other approaches | ||||
| Control | |||||
| #8 | February 22 | Collision avoidance | |||
| February 24 | Path planning | ||||
| #9 | March 1 | Decision making: exploration | |||
| March 3 | MDPs, POMDPs | ||||
| #10 | March 8 | Active Sensing and Reinforcement Learning | |||
| March 10 | Final Demo | Project 2 Due | |||