Swarm Robotic Path Planning In Intelligent Warehouse Scheduling

With the rapid development of e-commerce,the pressure of order distribution is huge,and intelligent warehousing technology has become the key to restricting the improvement of logistics efficiency.Intelligent robots as automation devices can replace manpower and improve the inefficiency of goods picking.Therefore,the path planning problem of swarm robots in intelligent warehouse scheduling is studied,which has both theoretical significance and application value.In this context,This paper presents a complete solution of intelligent warehouse system based on swarm robots.By solving the task planning,global path optimization and local path planning problems of swarm robots in intelligent warehouse,the swarm robots can move in the intelligent warehouse without collision and efficiently and complete the task of picking goods.First of all,analyze and build models of intelligent warehousing system and group robot system.The characteristics of the intelligent warehouse system and the group robot system are analyzed,the group robot system is controlled by the hybrid control method,and the simplified schematic model of the intelligent warehouse is established by using the grid method.Secondly,the task planning problem of swarm robots in smart warehouses is studied.Before the swarm of robots goes to the shelves for picking,the tasks in the system are planned as a whole to get the optimal picking order.In this paper,the task planning model of swarm robots is established,and the multi-strategy improved sparrow search algorithm(ISSA)is used to solve the problem.The superiority of the proposed algorithm is verified on 12 benchmark functions,and the task planning process and results are simulated by simulation.Finally,the path planning of swarm robots in smart warehouses are studied.Taking the shortest running time as the goal,the motion control is carried out with the improved A* algorithm considering the turning cost,and the search direction is pointed to the target point through the heuristic function to realize the global path optimization of the group robot;the cooperative traffic rules and reservation table are used to resolve the member robots.Partial path planning for member robots in case of local path conflicts during operation.At the end of this thesis,the simulation experiment of group robot path planning is carried out on the Matlab platform,and the simulation system of intelligent warehouse group robot picking is developed.Through a large number of repeated comparison experiments with existing algorithms,the effectiveness and superiority of the method in this paper are verified,which can effectively shorten the total consumption time and distance of swarm robots,and improve the efficiency of swarm robot systems and intelligent warehouse systems.