Safe Predictive Control of Four-Wheel Mobile Robot with Independent Steering and Drive

We propose a predictive controller that minimizes the trajectory error of a four-wheel mobile robot with independent steering and drive (4ISD) under safety constraints imposed by the presence of people. The 4ISD drivetrain is overactuated, that is, a given motion vector maps to multiple sets of actuation, not all of which are safe or optimal. We use convex optimization to satisfy Control Barrier Functions (CBF), which express the safety constraints for a robot operating in the vicinity of humans. The result is a Nonlinear Model Predictive Controller (NMPC) that produces a permissible actuation set. We develop mathematical foundations and run simulations that demonstrate the controller performance and safety around humans in the face of disturbances and uncertainties.