  This paper presents an approach to deal with safety of dynamical systems in
presence of multiple non-convex unsafe sets. While optimal control and model
predictive control strategies can be employed in these scenarios, they suffer
from high computational complexity in case of general nonlinear systems.
Leveraging control barrier functions, on the other hand, results in
computationally efficient control algorithms. Nevertheless, when safety
guarantees have to be enforced alongside stability objectives, undesired
asymptotically stable equilibrium points have been shown to arise. We propose a
computationally efficient optimization-based approach which allows us to ensure
safety of dynamical systems without introducing undesired equilibria even in
presence of multiple non-convex unsafe sets. The developed control algorithm is
showcased in simulation and in a real robot navigation application.

Systems and Control;Robotics;Systems and Control