An improved A* algorithm and its application in path planning for unmanned surface vehicles

An improved A* path planning method is proposed for inland-river garbage-collection unmanned surface vehicles (USVs) in complex flow fields. In static, flow-free environments, A* planning considers three objectives–shortest path, shortest time, and minimum energy consumption–and resulting paths are compared in length, sailing time, and energy use. For flowing water, a flow-adaptive heuristic incorporating flow direction is developed and its admissibility proven. A continuous instantaneous-angle energy-consumption model based on relative velocity is established. Three schemes–minimum energy, shortest time, and shortest path–are implemented. Simulations at 1.0 m/s flow and 3.0 m/s vessel speed show the minimum-energy path reduces energy use by about 3.5% versus the shortest-path strategy. Tests across multiple river channels confirm the improved A* outperforms RRT and PRM in path optimality, energy saving, computational efficiency, and environmental adaptability, offering a useful reference for autonomous USV navigation and decision-making under multiple constraints.