Research Status and Prospect of AUV Path Planning Algorithms

Abstract

Path planning algorithm is one of the core algorithms for autonomous underwater vehicle (AUV) to complete autonomous underwater cruise. In this paper, two kinds of AUV path planning algorithms based on environment modeling and path searching are reviewed. The domestic and foreign research status of environmental modeling methods such as grid method, visibility graph method and Voronoi diagram method is expounded, and their advantages and disadvantages are pointed out. In addition, the research results of predecessors in artificial potential field algorithm, fast marching algorithm, A* algorithm and other traditional path search algorithms are analyzed, and compared with the recent intelligent bionics path search algorithms such as particle swarm optimization algorithm, ant colony algorithm, genetic algorithm and artificial neural network algorithm. It is found that, in the face of the influence of complex underwater environment factors, improving the practicability of the algorithms in three-dimensional ocean environment such as ocean currents and complex obstacles, thus achieving AUV's efficient obstacle avoidance and energy saving is the focus of path planning algorithm research. Finally, the research trends of AUV path planning algorithm in intelligent development, fusion and multi-AUV collaboration, and the development of AUV remoteness for wide-area detection are prospected.

Keywords

• autonomous underwater vehicle (auv)
• environmental modeling method
• path search algorithm