Probabilistically Safe Controllers for Autonomous Systems Using Scenario-Based Model Predictive Control and Control Barrier Functions

This paper proposes a safety formulation that combines the strengths of model predictive control (MPC) and control barrier functions (CBFs) to design probabilistically safe controllers for autonomous systems in uncertain environments.