AUV 3D Path Planning Based on Improved Sparrow Search Algorithm
Yao Cheng, Wengang Jiang · 2024
In order to solve the problems of insufficient population diversity and local optimization in path planning of underwater unmanned vehicle (AUV) in complex three-dimensional underwater environment, an improved Sparrow search algorithm (ICSSA) based on Sparrow search algorithm was proposed. Firstly, Fuch chaotic mapping was used to initialize sparrow population, generate new initial population, and improve its population quality. Secondly, sine-wave strategy was introduced to update sparrow follower position, expand the population search range, and integrate chaos optimization algorithm for perturbation to improve the global search capability of the algorithm. Finally, through the simulation test, the experimental results show that the improved Sparrow search algorithm with chaotic optimization algorithm has good results in both local search ability and global search ability.