Kelvin Kan

End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers

Xingjian Li, Kelvin Kan, Deepanshu Verma, Krishna Kumar, Stanley Osher, Samy Wu Fung

We consider the problem of learning high-dimensional semi-global feedback controllers under hard safety constraints enforced by control barrier functions (CBFs). Incorporating CBFs into end-to-end policy training requires embedding a quadratic-program-based safety filter as an op…Read more