Local path planning for unmanned surface vehicle with improved artificial potential field method
Ma Xiao, Lin Zuan, Ruiyin Song · Journal of Physics Conference Series · 2020
Abstract Aiming at the drawbacks of traditional artificial potential field method in local path planning for USV (unmanned surface vehicle), an improved artificial potential field method is proposed. By improving the gravitational potential field model and restraining the distant gravitational potential field, the problem of USV colliding with obstacles is solved. In the repulsion field model, the influence factors such as relative position and relative velocity are introduced to reduce the repulsion potential field intensity of the obstacle near the target, so as to solve the problem of goal nonreachable with obstacle nearby. The regulation mechanism of random perturbation potential energy is introduced to solve the problem that it is difficult to move at local minimum points. The rationality and superiority of the proposed improved artificial potential field method are verified by simulation and comparison experiments.