The Path Planning Study of Autonomous Patrol Robot based on Modified Astar Algorithm and Genetic Algorithm - Liu, Jiaji; Xi, Bao; Chen, Si; Gao, Fang; Wang, Zhao; Long, Yujing (Chinese Control and Decision Conference, 2022)
A method combining modified Astar algorithm and genetic algorithm was proposed to search the shortest patrol path of autonomous patrol robot. A simplified method was used to transform GPS longitude and latitude coordinate into planimetric rectangular coordinate, which was converted to grid coordinate later. The shortest patrol path network between any two patrol points was constructed by the search results of Astar algorithm. The objective function of multipoint patrol path planning problem was established based on the shortest patrol path network, and the global optimal patrol path was obtained by genetic algorithm. The path searched by Astar algorithm was optimized by testing the visibility between two cells and removing the redundant nodes. Simulation results show that this method can effectively eliminate redundant nodes, shorten the path length, improve the smoothness of the path, and plan a better patrol path.