AUV 3D Path Planning Based on Improved PSO

The influence of ocean environment on navigation of autonomous underwater vehicle (AUV) cannot be ignored. In the marine environment, ocean currents, internal waves, and obstacles are usually considered in AUV path planning. In this paper, an improved particle swarm optimization (PSO) is proposed to solve three problems, traditional PSO algorithm is prone to fall into local optimization, path smoothing is always carried out after all the path planning steps, and the path fitness function is so simple that it cannot adapt to complex marine environment. The adaptive inertia weight and the “active” particle of the fish swarm algorithm are established to improve the global search and local search ability of the algorithm. The cubic spline interpolation method is combined with PSO to smooth the path in real time. The fitness function of the algorithm is optimized. Five evaluation indexes are comprehensively considered to solve the three-demensional (3D) path planning problem of AUV in the ocean currents and internal wave environment. The proposed method improves the safety of the path planning and saves energy.