Path Planning and Tracking Control of Unmanned Ship Based on Improved Artificial Potential Field Method and A-Star Algorithm

During the navigation process of unmanned ships, unmanned ships must be able to plan a reasonable path between the starting and the end point, and on the basis of this, the tracking tasks need to be completed. In response to this issue, this article proposes the planning method and tracking control method based on the improved artificial potential method and the unmanned ship path of the A-star algorithm. Adding a scaling factor to the repulsion function and combining the two algorithms effectively solves the problem that traditional artificial potential field methods are prone to local minima. After smoothing the planned path, it is used as the input of the controller. Based on the backstepping sliding mode method, the controller of the underactuated unmanned ship is designed, which solves the problem that the external environment cannot be considered in the traditional path planning. The effectiveness of path planning and tracking control of unmanned ships based on the improved artificial potential field method and A-star algorithm is verified by simulation experiments.