Research on Unmanned Ship Path Planning Algorithm Based on RRT* and Artificial Potential Field Method

In recent years, rapid progress in unmanned surface vessel (USV) technology has drawn widespread attention to the crucial aspect of path planning in USV navigation, both domestically and internationally. The Rapidly-exploring Random Tree Star (RRT*) algorithm is commonly employed for path planning. This paper presents improvements to the sampling strategy, node expansion method, and expansion step length of the RRT* algorithm. The enhanced RRT* algorithm is utilized for global path planning, significantly boosting its efficiency. When faced with unknown obstacles in the environment, the improved artificial potential field method incorporates repulsive potential field functions, augmented with the addition of virtual target points and obstacle size factors for local path planning. Through MATLAB simulation validation, the amalgamated algorithm demonstrates superior obstacle avoidance performance compared to individual algorithms, offering enhanced applicability to diverse environmental settings.