Path tracking and obstacle avoidance are essential for autonomous underwater vehicles (AUVs). During obstacle avoidance, AUVs must minimize path deviations and quickly return to the preset path. The weak maneuverability of AUVs increases the difficulty of obstacle avoidance. We propose an integrated path-tracking and obstacle-avoidance control method for AUVs. First, a path-based artificial potential field (PAPF) is introduced to enable simultaneous path tracking and obstacle avoidance for AUVs. Second, a repulsive potential field with self-adjusting magnitude is designed on the basis of the relative motion between the AUV and obstacles, effectively addressing the obstacle avoidance delay for weakly maneuverable AUVs. Third, virtual obstacle and moving obstacle velocity fields are created to solve the problems associated with dynamic obstacles and local minima in traditional APF methods. Simulations and real-world tests of the Hai Xiang-500XP AUV demonstrate that the PAPF method effectively integrates path tracking with obstacle avoidance, enhancing responsiveness and adaptability in dynamic environments.
Wang et al. (Sun,) studied this question.