为适应未来“四型机场”建设目标，进一步提升民航运输服务品质以及旅客日益增长的个性化需求，需要不断提升机场行李处理智能化水平。基于自主移动机器人（Autonomous Mobile Robot—AMR）集群的行李处理技术将是未来机场主要的智能化手段之一。本项目针对AMR集群规模配置、AMR全局最优调度、AMR实时路径规划等核心问题，研究机场各应用场景多要素对AMR集群规模配置的影响规律，研究能预测并合理配置AMR集群规模的方法。研究机场的行李信息数据关系，建立行李处理的优先级判定准则，探索出能够最优化任务分配及AMR调度策略的方法。研究基于机场应用场景的“长度-宽度-时间”三维时空模型，实现AMR集群在动态环境中的路径规划，解决冲突和死锁等问题，探索符合机场行李处理任务的AMR集群路径规划算法。研究成果将为未来机场行李处理技术的创新提供理论依据和实施方法。

In order to adapt to the “Four-Type Airport” development goals of CAAC in the future, further enhance the civil aviation service quality to meet the growing individual needs of passengers, it is necessary to continuously improve the intelligent level of airport baggage handling system. The new baggage handling system based on the AMR (Autonomous Mobile System – AMR) cluster technology will be one of the core intelligent technologies of the airport in the future. Aiming at the core problems of AMR cluster scale configuration, AMR global optimal scheduling and AMR real-time path planning, this project studies the effects regularity of the different airport application scenarios on the scale configuration of AMR cluster, and puts forward a method to predict and rationally configure the scale of AMR cluster. This project also studies the three-dimensional spatiotemporal model of AMR cluster based on different airport application scenarios, realizes the path planning of AMR cluster in dynamic environment, solves the conflict and deadlock problems, and explores the path planning algorithm of AMR cluster which conforms to the airport baggage handling operation. The research achievement will provide theoretical basis and implementation method for the future innovation of airport baggage handling technology.