Dynamic path planning for AGV based on Tent chaotic sparrow search algorithm

A dynamic path planning method of automatic guided vehicle(AGV) on the basis of the Tent chaotic sparrow search algorithm is proposed for the problems of population diversity reduction, easy to get caught up in local best and slow convergence during the iterative process of dynamic path planning solution of automatic guided vehicle (AGV). Based on the introduction of Tent mapping to initialize the individual sparrow positions to increase the initial population diversity; the global path optimality is improved and the convergence speed is accelerated by introducing the previous generation global optimal solution and adding adaptive weights m. The simulation results show that the proposed AGV dynamic path planning method has better convergence and solution accuracy, and the global search capability is greatly improved and a safe feasible path with optimal cost and satisfying constraints can be obtained quickly.