论文标题
通过自适应任务细分和调度，用于即时的机器人套件和交付的二重性优化
Bilevel Optimization for Just-in-Time Robotic Kitting and Delivery via Adaptive Task Segmentation and Scheduling
论文作者
论文摘要
套件是指准备和分组必要的零件和工具（或“套件”）以在制造环境中组装。自动化此过程可以简化人工工人的汇编任务，并提高效率。现有的自动化套件系统遵守脚本指令和预定义的启发式方法。但是，鉴于零件和逻辑延迟的可用性差异，现有系统的僵化性可以限制装配线的整体效率。在本文中，我们提出了一个双重优化框架，以使机器人能够执行基于任务分割的零件选择，套件布置和交付计划，以及时提供定制的套件 - 即在需要时正确。我们通过人类主题研究（n = 18）评估了提出的方法，涉及基于研究的数据构建平板家具桌和购物流仿真。我们的结果表明，与使用由任务图本身定义的刚性任务分割边界定义的基线方法相比，与基线方法相比，即将到来的套件更有效，对上游商店流量延迟具有弹性，并且比主观上更可取。
Kitting refers to the task of preparing and grouping necessary parts and tools (or "kits") for assembly in a manufacturing environment. Automating this process simplifies the assembly task for human workers and improves efficiency. Existing automated kitting systems adhere to scripted instructions and predefined heuristics. However, given variability in the availability of parts and logistic delays, the inflexibility of existing systems can limit the overall efficiency of an assembly line. In this paper, we propose a bilevel optimization framework to enable a robot to perform task segmentation-based part selection, kit arrangement, and delivery scheduling to provide custom-tailored kits just in time - i.e., right when they are needed. We evaluate the proposed approach both through a human subjects study (n=18) involving the construction of a flat-pack furniture table and shop-flow simulation based on the data from the study. Our results show that the just-in-time kitting system is objectively more efficient, resilient to upstream shop flow delays, and subjectively more preferable as compared to baseline approaches of using kits defined by rigid task segmentation boundaries defined by the task graph itself or a single kit that includes all parts necessary to assemble a single unit.
