论文标题
多工程推出，并改组仓库机器人路径计划
Multiagent Rollout with Reshuffling for Warehouse Robots Path Planning
论文作者
论文摘要
有效地解决大量机器人的路径计划问题对于现代仓库的成功运营至关重要。现有方法采用经典的最短路径算法来计划在与空间和时间相关联的环境中，以避免机器人之间的碰撞。在这项工作中，我们通过在较小的静态环境中模拟实现相同的目标。基于（Bertsekas，2021a）引入的新框架，我们建议使用重新安装算法进行多种推出，并将其应用于解决仓库机器人路径计划问题。所提出的方案具有坚实的理论保证，在我们的数值研究中表现出一致的表现。此外，它从通用推出方法继承了通过在线重新启动适应不断变化的环境的能力，我们通过一些机器人故障的示例来证明这一点。
Efficiently solving path planning problems for a large number of robots is critical to the successful operation of modern warehouses. The existing approaches adopt classical shortest path algorithms to plan in environments whose cells are associated with both space and time in order to avoid collision between robots. In this work, we achieve the same goal by means of simulation in a smaller static environment. Built upon the new framework introduced in (Bertsekas, 2021a), we propose multiagent rollout with reshuffling algorithm, and apply it to address the warehouse robots path planning problem. The proposed scheme has a solid theoretical guarantee and exhibits consistent performance in our numerical studies. Moreover, it inherits from the generic rollout methods the ability to adapt to a changing environment by online replanning, which we demonstrate through examples where some robots malfunction.
