Cooperative Path Planning of Multiple Unmanned Surface Vehicles for Search and Coverage Task

This paper solves the problem of cooperative path planning of multiple unmanned surface vehicles (USVs) for search and coverage tasks in water environments. Firstly, taking the search coverage problem of water surface pollutants as an example, the information concentration map is built to predict the diffusion of water surface pollutants. Secondly, we propose a region division method based on a Voronoi diagram, which divides the region and assigns it to each unmanned surface vehicle (USV). Then, on the basis of the traditional Model Predictive Control (MPC), the future reward index based on the regional centroid is introduced, and the Improved Salp Swarm Algorithm (ISSA) is used to solve MPC. Simulation results show the effectiveness of the proposed method.