Coordinated Path Planning Of Warehousing Multiple Mobile Robots Based On Conflict

At present,China's economic and social development has entered a new era.China's "New Four Great Inventions" represented by online shopping ha s made our lives more convenient and comfortable.Traditional warehousing distr ibution centers often rely on manpower to transport and sort goods.The task time is long and the work efficiency is low,which cannot meet the warehousing requirements of high-throughput.By establishing a warehousing system of multiple mobile robots,the efficiency of the entire storage center can be greatly improved,and the goods can be delivered to the customers more quickly.In order to enable the entire warehousing system to operate efficiently and safely,mobile robots must not have path conflicts during driving.Therefore,the coordinated path planning problem of multiple mobile robots is an important research direction.This thesis mainly studies the coordinated path planning problem between multiple robots in the mobile robot warehousing system.The thesis starts with a single robot path planning problem and find a better method for single robot path planning,and then apply it to multi-robot path planning problems.Aiming at the conflicts between multiple mobile robot paths,this thesis adopts a two-level path planning algorithm to plan an optimal driving path for each robot in the low-level search and solve the conflict between the robot paths in the high-level search.The robot is guaranteed to reach the target point without conflict at last.According to the different movement situation,the driving mode of the robot is also different.This thesis classifies it into uniform driving mode and non-uniform driving mode.The main difference lies in whether the time is divided into a single timestep an d whether each action of robot is executed in a single timestep.The thesis will apply the two-level path planning algorithm to study the coordinated path planning problem of multiple mobile robots under two driving modes respectively,and adopt the appropriate low-level search method according to the different driving mode.In the uniform driving mode,this thesis uses focal search to improve the algorithm.Without increasing the task completion time of the robot,we select the bounded suboptimal solution to reduce the number of extended nodes,so as to improve the path planning speed of the algorithm.In the non-uniform driving mode,this thesis improves the algorithm by taking into account the turning factor.Without increasing the driving distance of the robot,we reduced the task completion time by finding a path with fewer turning times,so as to improve the working efficiency of the robot.This thesis built the simulation environment of the warehousing system,compared the differences between the algorithms under different experimental conditions and analyzed the reasons.The simulation results show the effectiveness of the algorithm,and the improved algorithm achieves the expected effect.