基于互斥锁传播与多策略改进CCBS的多四向穿梭车路径规划与避障OA

To address the challenges of frequent path conflicts,steering delays,and high computational complexity in dense warehousing systems with multiple four-way shuttle vehicles,this study proposed a continuous conflict-based search algorithm enhanced by mutex propagation and multiple optimization strategies(M-MCCBS)to improve path planning efficiency and opera-tional stability.The high-level module integrated a mutex propagation mechanism and a focal search strategy to efficiently detect symmetrical conflicts and reduce the size of the constraint tree.At the low level,it improved the safe interval path planning al-gorithm through a node selection strategy,a minimum-turning strategy,and a dual-label strategy,which respectively reduced the number of expanded nodes,suppressed redundant steering actions,and reused early-stage computation results.Experimen-tal results demonstrate that the proposed algorithm outperforms the conventional continuous conflict-based search algorithm in terms of task completion time,steering frequency,and computational efficiency,achieving an average 9.83％improvement in task completion time.The results verify that the enhanced algorithm effectively balances solution quality and computational ef-ficiency,providing a practical and robust approach for multi-shuttle vehicle path planning in dense storage environments.