Research on Path Planning of Unmanned Surface Vehicle Based on Hybrid Algorithm

In both military and civilian fields, unmanned surface vehicles are widely used due to their small size, low cost, and versatility. Path planning technology is a key component of the unmanned vehicle technology system, which is crucial for unmanned vehicles to effectively respond to complex and changing work scenarios and tasks. This paper introduces a method that combines improved A* algorithm and dynamic window to optimize the path planning and dynamic obstacle avoidance capability of unmanned vehicles. By optimizing the heuristic function, expanding the search range, and smoothing the path, the efficiency and accuracy of path search can be improved. At the same time, the dynamic window method is used to real-time sample the status information of unmanned vehicles, optimize the path assessment function and select the most efficient trajectory to avoid dynamic obstacles. The simulation results show that this method can efficiently plan paths, avoid turning phenomena, and has the ability to respond quickly and avoid obstacles, effectively solving the real-time dynamic obstacle avoidance problem of unmanned vessels in autonomous operations at sea.