The purpose of this course will be to educate undergraduate and graduate students on state-of-the-art techniques in autonomous systems from both a theoretical and practical perspective. The key difference in this course and other courses taught in robotics, artificial intelligence, machine learning and control will be that it will eschew a purely practical focus that many of the other courses favor. It will instead teach students to reason about aspects such as safety, and reliability for autonomous systems using tools from control theory, formal methods, automata theory, artificial intelligence, and logic.
- Formal modelling and specification for CPS models
- Model-based verification and testing
- Various ingredients for autonomy based on AI techniques such as path planning, reinforcement learning
- Basics of the software stack for autonomous systems such as sensing, perception, communication, and feedback control