基于改进遗传算法的无人水下航行器路径规划OA

Aiming at the problems of unmanned underwater vehicles(AUVs)with many motion constraints as well as the low efficiency of path optimization and slow convergence speed of traditional genetic algorithm,an improved genetic algorithm path planning method for AUVs is proposed.The algorithm selects grid method to construct the environment,and uses path length,smoothness and dangerous area as evaluation function.The population initialization process of genetic algorithm is improved,the convergence speed is raised by introducing the grid of surrounding points,and the idea of catastrophe is combined to avoid the population falling into the local optimal solution.AUV smoothing process and deletion process are designed according to the constraints of AUV maximum turning angle to avoid sharp stop and turn of AUV navigation.The simulation and lake test results show that compared with the traditional genetic algorithm,the improved genetic algorithm reduces the path length by 11.4%,improves the convergence speed by 20.0%,and the convergence path meets the constraints of AUV navigation.