Safety-Critical Control and Path Following by Formations of Agents with Control Barrier Functions using Distributed Model Predictive Control

In this paper, we propose a safety-critical formation control method based on distributed nonlinear model predictive control strategy, which controls the path following and formation maintenance of the multiple mobile robots, while ensuring the collision avoidance. Firstly, we adopt the distributed framework with high real time performance. Secondly, based on the distributed optimization framework, discrete-time control barrier function constraints are transformed into smooth differentiable constraints to complete the polytopic obstacle avoidance with a small horizon by using the strong duality of convex optimization. Finally, the simulation results of three robots are given to prove the effectiveness of the proposed algorithm, and it can realize the local path generation based on real-time optimization in the narrow environment.