Decentralized Safety for Aggressively Maneuvering Multi-Robot Interactions

Abstract

This work provides a decentralized approach to safety by combining tools from control barrier functions (CBF) and nonlinear model predictive control (NMPC). It is shown how leveraging backup safety controllers allows for the robust implementation of CBF over the NMPC computation horizon, ensuring safety in nonlinear systems with actuation constraints. A leader-follower approach to control barrier functions (LF- CBF) enforcement will be introduced as a strategy to enable a robot leader, in a multi-robot interactions, to complete its task in minimum time, hence aggressively maneuvering. An algorithmic implementation of the proposed solution is provided and safety is verified via simulation.