This schedule is tentative and subject to change.
| DATE | TOPIC | READINGS | DUE |
|---|---|---|---|
| January 3 | Introduction and Course Overview | ||
| January 5 | Robots in an Uncertain World | ||
| January 7 | Discussion: Uber Accident Report (National Transportation Safety Board) | Reading | |
| January 10 | State Estimation, Bayesian Filtering | Prob. Rob., Ch. 1, Ch. 2 | |
| January 12 | Markov Localization | Prob. Rob., Ch. 5.2, Ch. 6 (through 6.3) | |
| January 14 | Discussion: Do Artifacts Have Politics? (Langdon Winner) | Reading | Project 1: Introduction |
| January 17 | Holiday: Martin Luther King Jr. Day | ||
| January 19 | Monte Carlo Sampling, Importance Sampling | Prob. Rob., Ch. 4 | |
| January 21 | Particle Filtering | Prob. Rob., Ch. 4 | |
| January 24 | The Kalman Filter | A New Approach to Linear Filtering, Prob. Rob., Ch. 3 | |
| January 26 | The Unscented Kalman Filter | The Unscented Kalman Filter | |
| January 28 | Discussion: Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction (Madeleine Clare Elish) | Reading | |
| January 31 | Introduction to Feedback Control | Underactuated Robotics Ch. 1 | |
| February 2 | PID Control, Pure Pursuit | Pure Pursuit, DARPA Challenge Controllers | |
| February 4 | Discussion: Robot Rights? Let’s Talk about Human Welfare Instead (Abeba Birhane) | Reading | Project 2: Localization |
| February 7 | Model Predictive Control | ||
| February 9 | Linear Quadratic Regulator | Underactuated Robotics Ch. 9, Notes on LQR by P. Abbeel | |
| February 11 | Discussion: Anatomy of an AI System (Kate Crawford, Vladan Joler) | Reading | |
| February 14 | Introduction to Planning | Planning Algorithms Ch 1, Ch 4.1-4.3, Ch 6.5, Ch 14.1 | |
| February 16 | Heuristic Search | A* | |
| February 18 | Discussion: Fairness and Abstraction in Sociotechnical Systems (Andrew D. Selbst et al.) | Reading | Project 3: Control |
| February 21 | Holiday: Presidents' Day | ||
| February 23 | Sampling-based Motion Planning | ||
| February 25 | Lazy Search, Planning for Vehicles | ||
| February 28 | MDPs 1 | ||
| March 2 | MDPs 2 | ||
| March 4 | Discussion: TBD | ||
| March 7 | Reinforcement Learning 1 | ||
| March 9 | Reinforcement Learning 2 | ||
| March 11 | Conclusion | Project 4: Planning |