Research On Path Planning For Multiple Mobile Robots In Intelligent Warehouse

Warehouse multi-robot system is an important part of intelligent storage.Currently,the research of multi-warehousing robots mainly includes task assignment,intelligent scheduling,autonomous obstacle avoidance and path planning.With the development of the standardized and rapid development of the logistics industry,storage robots are required to improve their work efficiency,complete route planning and intelligent obstacle avoidance,and achieve rapid access to goods.The paper simplified the artificial potential field method according to the structural storage environment,used it as the direction parameter of the ant colony algorithm and the A* algorithm search path,which accelerated the convergence speed of the ant colony algorithm and reduced the search scope of the A* algorithm.Speed up the storage robot's path planning and improved its work efficiency.Firstly,under the structural storage environment,through the force analysis of the storage robot in the artificial potential field and set the repulsion impact distance as a grid distance.The repulsion force of the robot is zero,that is,it only received the gravitational force.Used this gravity as a part of the ant colony algorithm heuristic information,changed the shortcomings of the early positive feedback mechanism of the ant colony algorithm,and accelerated the convergence speed of the algorithm.Secondly,selected multi-level control methods,used the improved ant colony algorithm for the pre-planning of multi-robot global paths,and then the A* algorithm is used for local path planning.Before calculates the A* algorithm's valuation function,set the angle threshold,and then calculated the angle between the vector formed by the parent node and the child node and the gravity of the target point received by the robot.Calculated the valuation function again of the node whose angle is smaller than the threshold.The node with the smallest evaluation function is used as the next parent node,and like this completed the local path planning.The blindness of the A* algorithm search is solved and reduced the search range of the algorithmThen,the improved A* algorithm is used to adjust the robot path when people and robots coexist in the warehouse.The robot acquired the movement information of people in the warehouse through the central controller.According to this,it introduced three new valuation functions: waiting time consumption of the robot,re-planning path consumption,and time consumption of following paths.By comparing the three periods the robot adjust its own operation status.Enables people to safely complete work in the normal operation of the storage system.Finally,the simulation results shown that the proposed method can speed up the convergence of the algorithm and decrease the search scope,which accelerated the storage robot's path planning and improved the work efficiency.