Path planning of unmanned surface vehicle based on artificial potential field approach considering virtual target points

Abstract

Aiming at the local minimum problem and target unreachable problems in the path planning of unmanned surface vehicle (USV), a path planning algorithm of USV considering virtual target point is proposed. For the target unreachable problem, a repulsive force potential field function is created. According to the measured distance between the target and the obstacle, the repulsive force of the target is zero, so that the USV can reach the target point. For the local minimum problem, the local minimum caused by various obstacles is analyzed, simulated annealing (SA) and artificial potential field approach (APFA) are combined to solve the minimum point problem caused by general obstacles. For the local minimum problem caused by special U-shaped obstacles, a virtual target point algorithm (VTPA) is established to solve this problem. The simulation results prove that this algorithm solves the problem of long path caused by too large repulsive force. Compared with Dual-Tree Rapidly exploring Random Tree (DT-RRT) algorithm, the efficiency of this algorithm has been significantly improved. Algorithm running time was reduced by 33.4%. Path length was reduced by 17.8%. Not only the time is saved, but also the path planning is optimized, so that the speed of the algorithm is accelerated.