Global Path Planning for Ability Storm Robot

Based on Messy genetic algorithm (Messy GA), a general path planning algorithm for mobile robots is designed in which the optimized objects include the shortest path, the fine smoothness and the optimal safety distance. Optimized operators and the adaptive adjustment of the crossover rates and mutation rates are added into the algorithm in order to improve the convergence rate. Simulation results verify the efficiency of the proposed method. According to the practical operation requirements of ability storm robot (AS-R), the algorithm is modified to increase the distance between path and obstacles, and a smoothing method is introduced to optimize the path. The trajectory tracking experiments are conducted with the AS-R robot as the platform. The experiment results show that the algorithm can plan the paths in lab environment with randomly placed obstacles, and can realize the global path planning for AS-R robot finally.