Access Strategy and Path Planning based on Planar Mobile Stereo Garage

Taking the planar mobile stereo garage as the research object, in order to improve its overall access efficiency, combined with the operation characteristics of the garage, this paper studies the access strategy and Automated Guided Vehicle (AGV) path planning. Firstly, considering the actual access process of the garage and the different access conditions in the flat peak, storage peak and pickup peak periods, the mathematical model of access strategy is established, and the access strategy suitable for the garage is selected through calculation and analysis. Secondly, based on the traditional grey wolf optimization (GWO) algorithm, an improved GWO algorithm based on initial population opposition-based learning and two-stage nonlinear convergence factor is proposed and applied to the static obstacle avoidance path planning problem of AGV in the stereo garage. Compared with the genetic algorithm and the traditional GWO algorithm, the results show that the improved GWO algorithm has outstanding performance in terms of convergence speed, path length.