Path planning of surface unmanned craft based on variable step-length sparse A-star algorithm

In order to further improve the speed of path planning for surface unmanned craft and the ability to find the shortest voyage, the article proposes a path planning method based on variable step sparse A* algorithm. By analyzing the existing shortcomings of the three path planning methods of Dijkstra algorithm, A* algorithm, and sparse A* algorithm, the cost function, search space, and exploration step length of the traditional A* algorithm are improved to reduce the complexity of the algorithm. Carry out the simulation experiment of ships entering the port and berth, and carry out the navigation simulation experiment on the rasterized chart of a certain sea area of Zhoushan Islands. During the path exploration, a dangerous avoidance zone of 1 nautical mile is generated around all obstacles to ensure the authenticity of the experiment. safety. The results show that the variable-step sparse A* algorithm concisely and efficiently realizes the path planning of complex waters, shortens the search time by 80% compared with the A* algorithm, and has a shorter path and better robustness.