Multi-UUV Coordinated Path Planning with Collision Avoidance (CPP/CA) Based on Combination of Improved APF and A⁎

Aiming at the path planning problem of cooperative underwater unmanned vehicles (UUVs) in the obstacle-constrained environment, this paper proposes a new obstacle-avoidance path planning algorithm. This algorithm combines artificial potential field (APF) method and A
^⁎
algorithm, which can realize multi-UUV coordinated path planning with collision avoidance (CPP/CA). Different from the current APF, this algorithm increases the repulsion between UUVs on the basis of optimizing the repulsive force of obstacles, sets temporary virtual target points, and uses the A
^⁎
algorithm to make UUVs pass through obstacles smoothly and move to the target point. This algorithm not only solves the issue of UUV falling into a local minimum, but also considers UUV companions to perform the same task, so that each UUV individually changes its path to avoid collisions with other UUVs and obstacles. Experimental simulation results show that the proposed algorithm has better obstacle avoidance performance and the ability to track targets, which can greatly improve the success rate of path planning.