Research On Multi AGV Path Planning And Collision Avoidance Strategy For Intelligent Storage

Along with the demand of logistics industry and the development of technology,AGV has been more and more applied to handle and pick goods in intelligent storage.The effective work of AGV in intelligent warehousing is inseparable from the path planning,especially multi AGV path planning,which needs to consider the constraints of time,distance and so on,so as to avoid conflicts between AGVs and their obstacles.Multi AGV path planning has become a key research content in the field.Artificial potential field method and ant colony algorithm are applied in this paper,and priority and rate regulation methods are combined to AGV path planning.The main contents of the study are as follows:First of all,this paper expounds the development of intelligent warehousing,path planning problems and related algorithms.According to the setting of storage environment and the characteristics of AGV operation,the environment model is established by grid method.AGV path planning model is established to minimize the travel time cost,considering the different travel time cost of going straight,turning and accelerating,so as to plan the optimal path for AGV in intelligent storage.Then,aiming at the disadvantage that the artificial potential field method can not ensure the global optimal solution,the artificial potential field method is improved and combined with the ant colony algorithm to solve the AGV path planning model.About collisions between AGV paths,the collision types are judged according to the different nodes before and after the conflict nodes.In addition,the strategy of accelerating or re-path planning are adopted to solve the AGV collisions by combining priority.Finally,based on the actual situation of intelligent storage system,a case is given and the grid map of storage environment of 30*30 is established.A number of task orders are generated.The model of AGV path planning model is built and simulation is conducted.The simulation results are analyzed,so as to verify the feasibility of collision resolution strategy.The improved potential field ant colony algorithm is compared with the traditional ant colony algorithm to verify its feasibility.