Application of Improved Genetic Algorithm to Unmanned Surface Vehicle Path Planning

Abstract

Lake patrol is an important part of lake water environment management and the path planning is the key problem to lake patrol. In order to solve this kind of path planning problem, an improved genetic algorithm is proposed. A new initial population method is proposed to create a better quality of the initial population, and the adaptive crossover probability and mutation probability are designed. In this paper, the grid method is used to construct the working environment of the lake patrol unmanned surface vehicle (USV). Compared with the traditional genetic algorithm, the improved genetic algorithm can obtain the shorter and safer non-collision path in different lake environments. The simulation results demonstrate that the path planning of the lake patrol USV with the improved genetic algorithm is reasonable and effective.