This course will teach mathematical and algorithmic techniques and tools for building safe autonomous systems, from unmanned drones to self-driving cars to medical devices.
The course is split into three modules:
- Systems: how to understand and formally represent a complex autonomous system? Mathematical formalisms for dynamical, probabilistic, and hybrid systems.
- Autonomy: how to enable autonomous operation in a challenging environment? Data-driven components, probabilistic graphical models, neural networks, errors/robustness of learned models, learned perception/control.
- Safety: how to ensure that an autonomous system behaves safely? Logical specifications of safety, verification of system models and learned components, safe planning and control, temporal and confidence monitoring.
Credits: 3.
See the syllabus for details. Feel free to reach out if you have any questions about the course or your participation in it.
If you are interested in the teaching materials, please reach out as well.