Path planning method for unmanned surface vehicle with controllable distance from obstacles

In order to solve the problems of safety and smoothness in the path planning of an unmanned surface vehicle (USV), a path planning method with a controllable distance from obstacles is proposed.

First, the raster environment information is generated in combination with the radar image, and the Voronoi field algorithm (VFA) is used to add the danger potential field to each grid and establish the navigation boundary; second, the risk function associated with the navigation boundary is established to improve the evaluation function of the A-star algorithm, and the improved A-star algorithm is used for path planning; finally, for the problem of the large course altering of the navigation path, the gradient descent method (GDM) is used to plot a continuous smooth navigation path that satisfies the actual navigation requirements of the USV.

The simulation results show that the proposed path planning method can control the distance between the path and obstacles by setting different navigation boundaries, and the smoothness meets the navigation requirements.

The method proposed herein is reasonable and effective in the path planning process of USVs, and can provide references for USV autonomous obstacle avoidance decision-making.