| Large-scale pre-warehouse is an important part of e-commerce platform to realize material distribution,and the efficiency of warehouse sorting operation is an important standard to reflect the sorting ability of pre-warehouse.Traditional pre-warehouse picking mostly relies on intensive manual operation.Because of its low efficiency,chaotic management and high error rate,it no longer conforms to the characteristics of many types and small batches of e-commerce logistics,and can not meet the requirements of modern enterprises for pursuing high efficiency,convenience and economic profit.This requires the combination of computers and intelligent equipment to transform the pre-warehouse into a digital and automated modern warehouse.In this thesis,the mechanical structure of the storage AGV is designed by taking the e-commerce pre-warehouse as an example.At the same time,based on the fishbone layout,the picking path of AGV in the pre-warehouse is optimized by using an improved algorithm.(1)Design of mechanical structure: According to the environmental conditions and functional requirements of e-commerce storage,the walking and transplanting modes of AGV are studied,and after determining its specific parameters,the modular design of storage AGV structure is divided into vehicle design,drive design and jack-up design,and it is introduced in detail.Finally,the three-dimensional structure model of AGV is established.(2)Finite element analysis of structure: The AGV structure established is imported,and the frame is statically analyzed based on simulation software,and the parts meet the strength requirements through stress and deformation diagrams.The modal analysis of the whole structure is carried out,and it is determined by the modal diagram that the road surface and external excitation will not cause the resonance phenomenon of the structure;Finally,the results of statics analysis,load spectrum and structural material properties are imported into analysis software for setting,analysis and calculation,the fatigue life and fatigue damage of the structure are predicted.(3)Two-point path planning: In order to determine the walking path of AGV,firstly,aiming at the shortcomings of slow optimization efficiency and poor path feasibility in ant colony algorithm,dynamic A star evaluation function,gradient pheromone increase and adaptive change of volatilization coefficient are added to improve the convergence speed and global optimization ability of the algorithm,and then the obtained path is processed by cubic B-spline curve to improve the path smoothness.Finally,based on programming simulation software,the validity of the algorithm is verified by comparing with the standard algorithm.(4)Picking path planning: take the fishbone layout as the pre-storage layout,and use the improved ant colony algorithm to find the optimal path and distance of any two points in the environment,so as to construct the distance matrix between picking points;Considering the carrying capacity of AGV and the uncertainty of order data in reality,the genetic allocation strategy of real-time orders and path planning of ant colony algorithm are adopted to design and solve the picking path problem of multi-single and multi-vehicle.Finally,the overall completion time and overall path length of S-type picking strategy and genetic-ant colony algorithm strategy are analyzed to verify the superiority of this method. |
