Global Path Planning for AUV Based on Sparse A* Search Algorithm

Classical autonomous underwater vehicle (AUV) path planning algorithms, such as artificial potential field method and graph search algorithm, often result in the problems of easily converging on local optimum and low calcula-tion speed. To solve the problems, a new method for distributing random points is proposed based on the sparse A* search algorithm for constructing search space, where a random function is used to evenly distribute enough search nodes in the path planning area. This method can obviously reduce the calculation work and increase the search effi-ciency. After the original path is deduced, an intervisibility test is conducted to reduce the path turning points and get an optimal path. Simulation result shows that the proposed method is feasible and valid, and it features better global opti-mization and higher calculation speed.