AGV Path Planning Based on Improved Hybrid Artificial Fish Swarm Algorithm

To solve the problems of slow convergence speed and many path inflection points in AGV path planning, an AGV path planning method based on improved hybrid artificial fish swarm algorithm(IHAFSA) is proposed. Firstly, the sparrow search algorithm and the artificial fish swarm algorithm are used to jointly construct the initial population to improve the population diversity of the algorithm; secondly, adaptive step size, field of view and crowding factor are added to the algorithm to balance the global and local search ability of the algorithm; finally, the fitness function is used to traverse the locally optimal solutions within the field of view, and the resulting locally optimal solutions are used to improve the traditional prey behavior and to exclude the interference of the suboptimal solutions. The results show that the algorithm has good planning results in terms of convergence speed, number of path inflection points and total path length.