Research on global path planning of unmanned surface vehicles based on improved A* algorithm

Abstract

In path planning for unmanned surface vehicles, the classic A* algorithm has the drawbacks of having more redundant nodes, more search nodes, and being close to obstacles. Combined with the navigation characteristics of unmanned surface vehicles, the A* algorithm is improved from four aspects. Firstly, to ensure the security of the planed path, the evaluation function considers the influence of obstacles repulsion fields. Secondly, when searching nodes, the expansion directions of the node are optimized while taking into account the target node's direction information. Thirdly, the shortest distance from the obstacles grids to the connection between the target node and the current node is computed. If the distance is less than the safety distance, the A* algorithm's search process is jumped out to increase search efficiency. Finally, to lessen the number of turning points, the redundant nodes of the planned path are finally deleted. The simulation results show that there are obvious advantages in the number of turning points, the security of the path, and the number of traversal nodes.