ECE 498 SMA

Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 0 to 4 undergraduate hours. 0 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

This course introduces key algorithms and techniques for performing safety analysis of powerful autonomous systems such as autonomous cars, delivery drones, and manufacturing robots. Specifically, we introduce key algorithms in sensing, perception, control, and analysis, with a view towards understanding their basic assumptions and performance guarantees. What are the assumptions and what can be guaranteed by these modules? How to combine assumptions and guarantees of individual modules to make compositional arguments about system-level safety and assurance cases? The course also provides exposure to some of the state-of-the-art software tools for sensing, control, modelling, and analysis. Our approach will be to cover one or two algorithms / approaches in each topic and discuss their correctness arguments and performance trade-offs. Students will get experience with latest tools through labs and home works and they will perform hand-on laboratory work on the Polaris GEM autonomous veh