Application of improved RRT algorithm in unmanned surface vehicle path planning

Due to the complex and changeable marine environment, in order to ensure the safety of seafarers and comprehensively improve the governance of the marine field, the topic of unmanned ships has become more and more popular in recent years. The research of unmanned ships has also been an important topic in the navigation field in recent years. The ability of unmanned ships to avoid collision path planning is one of its key technologies and an important manifestation of its intelligence. Aiming at the path planning problem of unmanned ships in known environmental maps, this paper uses mathematical modeling software to simulate some algorithm fields of unmanned ships' path planning, and compares the running results of related algorithms. Rapidly-exploring Random Trees (RRT) algorithm is an efficient planning method in a multi-dimensional space. In this paper, the RRT algorithm is improved and applied to the path planning problem of unmanned ships, and then compared with the traditional RRT algorithm. Experimental results show that the path length of the improved RRT algorithm is shorter and smoother than that of the traditional RRT algorithm. It is proved that the improved RRT algorithm can more effectively complete the path planning of the unmanned ship.