Swarm control with collision avoidance for multiple underactuated surface vehicles

In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy.