动态订单下机器人协同取货，效率提升显著。
Dynamic Multi-Agent Pickup and Delivery in Robotic Cellular Warehousing Systems
- 基于令牌传递机制，实现订单更新时的实时重规划
- 新加入货品可由空闲机器人协助，降低整体完成时间
- 适用于需要快速响应订单变化的智能仓储系统
机器人细胞仓储系统（RCWS）催生了多机器人取货配送（MAPD）过程，其中机器人需为每笔订单顺序取多个库存单位（SKUs）。与传统假设任务静态的MAPD不同，实际仓储中订单常动态演变，即在执行过程中新增SKU。本文首次提出考虑内部订单演化的动态多机器人取货配送问题。基于令牌传递（TP）机制，提出两种事件触发的在线重规划算法：动态TP允许机器人在订单更新后从当前执行状态出发，通过优先级感知的令牌获取进行重规划；合作TP进一步使空闲机器人能协助新增SKU，同时保留原订单所有权。仿真结果表明，所提方法相比静态和非协作基线显著降低订单流经时间，从而提升RCWS整体效率。
原文摘要 · Abstract (English)
Robotic Cellular Warehousing Systems (RCWS) give rise to multi-agent pickup and delivery (MAPD) processes in which robots sequentially collect multiple stock-keeping units (SKUs) for each order. Unlike classical MAPD formulations that assume static tasks, real warehouse operations often involve dynamic order evolution, where new SKUs may be appended to an order while it is being executed. Motivated by this practical requirement, this letter formulates the Dynamic Multi-Agent Pickup and Delivery problem considering internal order evolution for the first time. Building on the token passing (TP) mechanism, we propose two event-triggered online replanning algorithms. The first, Dynamic-TP, enables an event-triggered dynamic response by allowing robots to replan from their current execution states through priority-aware token acquisition after order updates. The second, Cooperative-TP, further enables idle robots to assist newly added SKUs while preserving the original order ownership. Simulation results demonstrate that the proposed methods significantly reduce order flowtime compared with static and non-cooperative baselines, thereby improving system-level efficiency in RCWS.
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