Research on AGV Scheduling Based on Point-to-Point Mode

In order to solve the problem of AGV routing optimization in intelligent workshops, in this paper, an improved genetic algorithm is proposed to optimize AGV walking path. The smoothness function is added to the fitness function of traditional genetic algorithm, the improved genetic algorithm not only requires the shortest path, but also can control the turning angle of AGV, The walking path of AGV is smoother, safer and more efficient while ensuring the good global searching ability and robustness of genetic algorithm itself. Experimental results show that, compared with the traditional genetic algorithm, the proposed algorithm not only has a shorter walking path, but also has a smoother path. The feasibility of the algorithm is verified.