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