Energy-Saving Path Planning for AUVs in Current Environment Based on Improved PSO-Lévy Algorithm
To obtain energy-saving obstacle avoidance paths of autonomous undersea vehicles(AUVs)in the current environment,a three-dimensional dynamic current environment model based on current field velocity information and underwater topographic obstacles was established.The augmented objective function was established based on navigation energy consumption,AUV maneuvering performance,and obstacle constraints,and an improved particle swarm optimization-Lévy(PSO-Lévy)algorithm based on weight adjustment mechanism and random wandering mechanism was proposed.The parameter adjustment strategy based on the optimal damping ratio and the random step wandering strategy based on the Lévy-flight process were introduced into the PSO algorithm.By executing a long-step wandering operation and regulating the velocity inertial of particles with a certain probability,the PSO algorithm could get a longer step and jump out of the local optimum.The simulation results show that the proposed algorithm can plan the optimal path with low energy consumption according to the current information while effectively avoiding obstacles.
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