Optimal Coverage Path Planning for Unmanned Surface Vehicles Using Flexible Formation Tracking Control

Unmanned surface vehicle (USVs) have attracted significant attention in cooperative surveys of marine environments, where efficient coverage path planning (CPP) is crucial. This paper introduces a novel CPP method integrating flexible formation control to enhance the exploration capabilities of USVs in complex marine environments. The proposed method first divided the irregular target area into convex sub-regions using a convex decomposition, and the optimal visiting sequence was determined using a traveling salesman problem (TSP) approach with a genetic algorithm. Traditional back-and-forth search paths were then used for local coverage. A flexible formation tracking control was developed to enhance coverage efficiency, dynamically adapting the USV formation according to the geometry of the sub-region. The simulation results validated the proposed method in various scenarios, including convex and non-convex regions with obstacles. Compared to the fixed formation approach, the proposed flexible formation tracking control method improved the coverage rates by up to 1.8% and reduced the redundant coverage by up to 4.8%. Therefore, the proposed flexible formation control method helps improve the efficiency of multi-USV cooperative coverage operations. Future research will extend the proposed approach by incorporating environmental disturbances and operational constraints to increase robustness in real-world maritime applications.