An improved artificial potential field method-based obstacle avoidance strategy is proposed for the obstacle avoidance challenges faced by underwater vehicles in complex underwater environments,such as the local optimal solution trap and the unreachable target point.The strategy firstly improves the path exploration ability of the submarine in dynamic environment and the escape ability of local optimal traps by incorporating the random perturbation mechanism;then,in order to solve the problem of unreachable target point,a target adjustment factor is innovatively introduced into the strategy,which ensures that the repulsive force decreases to zero when the vehicle approaches the target by finely adjusting the equilibrium relationship between the gravitational force and repulsive force,and by optimizing the cut-off value of the gravitational force segmentation function and the radius of repulsive force influence,so that the vehicle can accurately and stably arrive at the target point.The experimental results show that the success rate of obstacle avoidance is significantly improved compared with the traditional artificial potential field method,and the arrival rate of the target point reaches 100%.The results not only verify the efficiency and reliability of the proposed strategy in complex obstacle avoidance tasks,but also explore a new and efficient obstacle avoidance method for the autonomous navigation technology of underwater vehicles.
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