Improved Snake Optimization and Particle Swarm Fusion Algorithm Based on AUV Global Path Planning

An improved snake optimization algorithm (ISO) is proposed to obtain an effective and reliable three-dimensional path for an autonomous underwater vehicle (AUV) to navigate seabed barrier environments and ocean currents. First, a three-dimensional seafloor environment model, seafloor obstacles, and a model of a Lamb vortex current are constructed. Second, the designed mathematical framework for three-dimensional path planning comprehensively considers a variety of constraints such as sailing distance, path threat, sailing altitude, and optimized ocean current energy consumption. Finally, ISO diversifies the snake population’s distribution space by implementing a good point set initialization approach, a Cauchy variation strategy to enhance the convergence accuracy, and a fusion particle swarm algorithm strategy to improve the convergence speed. To evaluate ISO’s optimization performance, by minimizing the fitness value, the optimization outcomes are contrasted with those of five different algorithms. The experimental results show that the ISO algorithm can generate safe, low-energy, and path-optimal AUV navigation planning, which presents a novel effective approach for AUV path planning.