A Three-Dimensional Path Planning System for AUV Diving Process Considering Ocean Current and Energy Consumption

This paper provides a three-dimensional (3D) path planning system for autonomous underwater vehicles (AUVs) to accomplish the feasible diving process with less energy and restricted motion rotation angle in complex marine environment. Aiming at the limitation of traditional A* algorithm in high dimensional environment and local extremum, a constrained sampling A* (CSA*) algorithm with spatial boundary is developed to simplify the 3D environment modeling process and improve the search efficiency. The CSA* is combined with adaptive quantum-behaved particle swarm optimization (AQPSO) algorithm to reduce the energy consumption under the influence of ocean currents. Considering the kinematic limit, AQPSO is constrained by a series of proposed attitude correction laws to ensure the feasibility of the path result. The proposed method is tested in multiple numerical scenarios and compared with four typical evolutionary algorithms. The simulation results verify that the optimization ability and stability of the proposed planning system are the best among the methods compared in this paper, and it can well balance the relationship between route feasibility and energy consumption, and guide the vehicle to move towards underwater target points.