A path planning algorithm for mobile robot based on water flow potential field method and beetle antennae search algorithm

Aiming at the problems that beetle antennae search algorithm is difficult and easy to avoid obstacles when solving path planning problems, and falls into local optimization, which leads to low efficiency, a path planning algorithm of mobile robot combining the water flow potential field method and the beetle antennae search is proposed. Path planning divides the global path into segments by setting up segmented sites by using the beetle genetic operator. Local path planning between sites is classified according to the characteristics of obstacles, and the artificial potential field method is used to guide the search. The nature of water flow method is used to plan the obstacle avoidance route, optimize the obstacle avoidance process, and effectively avoid falling into local trap obstacles. Finally, the site coordinates are optimized by the beetle antennae search algorithm to improve the path quality and prevent the path from falling into local optimum. The simulation results show that the algorithm can effectively avoid obstacles in various path planning environments, has the characteristics of short time consumption, good optimization effect, and is not easy to fall into local optimization, and is an efficient algorithm for solving the path planning problem of mobile robots.