Research On Conflict-Free Multi-Vehicle Scheduling Strategy For Warehouse System

Conflict-free scheduling of multiple robots is at the heart of intelligent storage systems.As the size of the warehouse continues to expand,the number of robots gradually increases,the system runs complex processes,problems are closely linked,and multiple robots can cause serial conflicts and congestion,or even deadlock phenomena.Most current research reduces the scope of conflict in terms of path planning,but fails to thoroughly optimise conflict from a global perspective,and can only qualitatively reduce conflict rather than quantitatively eliminate it.Moreover,there is a lack of path optimisation strategies that can be applied to multiple scenarios at this stage,and the conflict strategy cannot be changed adaptively according to different warehouse demands,which limits the efficiency of transporting high-demand goods.Therefore,this paper focuses on three aspects of multivehicle scheduling: conflict-free scheduling,order picking,and conflict avoidance.First of all,this paper establishes a multi-robot path planning model.The raster map method is used to build the warehouse map,while the reservation table is optimised and redesigned to reduce memory occupation and improve the efficiency of multi-vehicle path conflict tracking detection;the A* algorithm is improved by adding waiting time and steering time to more accurately predict and plan robot paths;the task allocation strategy and multivehicle collision avoidance strategy are improved to establish a conflict-free scheduling model for multiple robots and realise efficient path planning for multiple robots at the same time.The algorithm is also used to improve the task allocation strategy and multi-vehicle collision avoidance strategy,to establish a conflict-free scheduling model for multiple robots,and to achieve efficient control of multiple robots’ path planning.Secondly,to address the problem of prolonged congestion in some road sections due to over-concentrated route planning during multi-vehicle order transportation,this paper innovatively proposes to introduce the heat map algorithm into the path planning algorithm,track and monitor the congestion level of each lane of the intelligent warehouse system in real time,determine the matching rules between robots and orders and picking stations,and realise an efficient multi-robot conflict-free scheduling solution.Again,to address the problem of different picking requirements in different scenarios resulting in lower outbound efficiency,this paper investigates dynamic adaptive order picking strategies in different warehouse systems,innovatively proposing the introduction of the HAC algorithm into the smart warehouse system,based on historical order data,similarity aggregation of data,and using this to analyse the degree of demand for goods in current orders,the order of current orders is rearranged according to the degree of demand for goods The order is re-arranged in descending order,so that goods with high demand can be released in the first batch of the current order.Finally,in order to solve the problem of multiple robots passing through the intersection when there is a conflict,this paper innovatively proposes a dynamic weighting table method,which assigns weights to the current state of the robots based on the current demand degree of goods delivered by the robots,the process of entering and leaving the warehouse,the remaining time of the path and other dynamic information,forming a dynamic weighting table.The dynamic weighting table is then used to make intelligent decisions about the order of robots passing at conflicting locations.In summary,this paper integrates a complete and efficient set of intelligent storage scheduling strategies that can be applied to multiple scenarios: the proposed multi-robot conflict-free scheduling method based on the heat map algorithm,which can improve global transport scheduling efficiency;the proposed multi-robot path optimisation strategy based on HAC order ordering,which can realise a dynamic adaptive multi-robot collision avoidance strategy;and the proposed dynamic weighting table method,which can intelligently decide the order of robots passing at conflicting locations.