An AUV Path Planning Method Based on Improved APF-RRT*

Path planning plays an important role when an Autonomous Underwater Vehicle (AUV) is performing a cruising task such as underwater Simultaneous Localization and Mapping (SLAM). A path planning method accomplish the goals of avoiding obstacles and finding shortest paths, but may meet the problems that the AUV trapped into local optima and low efficiency. A novel path planning method based on APF-RRT* is proposed, which introduces gravity and repulsion functions of the APF algorithm to the RRT* algorithm. The proposed method avoids the problem of local optima trapping and low efficiency. Considering the impact of water flow and the movement of dynamic obstacles on the AUV, these two factors are introduced to the gravity and repulsion function, which improves the effectiveness of the algorithm in the underwater environment. Furthermore, Bézier curve is used to smooth the planned path to make the path more consistent with the kinematics of the AUV. The simulation results show that this algorithm can quickly complete path searching and generate reachable paths in both static and dynamic underwater environments. After path optimization, it is more suitable for AUV driving and operation in underwater environments.