Underwater 3D Path Planning for AUV in Ocean Currents Based on Improved Informed RRT* Algorithm
Enjiao Zhao, Tingting Cheng, Shixiong Wang, Xuehang Lin
Abstract
Aiming at the problems of blind search, low environmental adaptability, and long path that exist in the Informed RRT* algorithm for AUV underwater 3D path planning, this paper introduces an improved version of the Informed RRT* algorithm. This enhanced algorithm introduces an adaptive step size to enhance the applicability and reduce the iteration count. Additionally, a bidirectional extension strategy is employed in the initial phase to minimize the time required for searching the initial path, and an angle constraint is added to improve goal-point orientation and search efficiency. A goal-directed sampling strategy is incorporated to further increase the efficiency of tree growth toward the goal point. Furthermore, a pruning strategy is used to optimize the found path by shortening the path length and reducing the number of path nodes, thus enhancing the smoothness of the path found by the algorithm. In this study, the underwater 3D environment modeling considers both the seabed topography and ocean currents, with ocean current information extracted and interpolated. The path length and the influence of ocean currents are taken as indicators to evaluate the path in the objective function. Simulation results demonstrate that the improved Informed RRT* algorithm provides a more effective solution for AUV underwater 3D path planning.