UUV Path Planning Based on GA-AFSA Algorithm

Abstract

In solving the issue of efficiency in global path planning of UUV underwater multi-task points, and reduce energy and time consumption during task execution, a hybrid GA-AFSA algorithm was constructed based on the Genetic and Artificial Fish Swarm Algorithm. Maximize the advantages of genetic algorithm global rapid convergence and artificial fish swarm algorithm with high solution accuracy, to solve the initial population generation and optimal path solution problems in UUV path planning, then a comparative experiment between the genetic and the GA-AFSA algorithm is put into effect. The experimental results show that the GA-AFSA algorithm takes into account both the global search ability and the fast search performance, compared with the improved GA algorithm, its best iteration time is reduced by 41%, the optimal path length is reduced by 16%, it has the advantages of fast optimal solution rate and shorter optimal path solution, and has strong efficiency and practicability.