This paper proposes a control method for the multi-agent pickup and delivery problem (MAPD problem) by extending the priority inheritance with backtracking (PIBT) method to make it applicable to more general environments. PIBT is an effective algorithm that introduces a priority to each agent, and at each timestep, the agents, in descending order of priority, decide their next neighboring locations in the next timestep through communications only with the local agents. Unfortunately, PIBT is only applicable to environments that are modeled as a bi-connected area, and if it contains dead-ends, such as tree-shaped paths, PIBT may cause deadlocks. However, in the real-world environment, there are many dead-end paths to locations such as the shelves where materials are stored as well as loading/unloading locations to transportation trucks. Our proposed method enables MAPD tasks to be performed in environments with some tree-shaped paths without deadlock while preserving the PIBT feature; it does this by allowing the agents to have temporary priorities and restricting agents' movements in the trees. First, we demonstrate that agents can always reach their delivery without deadlock. Our experiments indicate that the proposed method is very efficient, even in environments where PIBT is not applicable, by comparing them with those obtained using the well-known token passing method as a baseline.
翻译:本文建议了多试剂接货和交货问题(MAPD问题)的控制方法,通过扩展带回跟踪(PIBT)的优先继承方法,使其适用于更普遍的环境。 PIBT是一种有效的算法,它为每个代理提供优先,每次按时间顺序排列,代理在下一个时段通过仅与当地代理进行通信,决定其下一个邻接地点。不幸的是,PIBT只适用于以双连接区域为模范的环境,如果它含有树形路径等死端,PIBT可能会造成僵局。然而,在现实世界环境中,材料储存的架子等地点有许多死端路径,运输卡车的装载/卸载地点。我们提出的方法使MAPD的任务能够在不陷入僵局的环境中进行,同时保持PIBT的特征;它允许代理拥有临时优先事项并限制代理在树木中的移动。首先,我们证明代理人总是能够不陷入僵局地到达他们的交货地点。在现实世界环境中,我们提出的实验表明,在采用非常有效的基准环境的情况下,我们所了解的是,这些基准是经过了非常有效的环境。