Algorithm for Robotic Picking in Amazon Fulfillment Centers Enables Humans and Robots to Work Together Effectively

IF 1.1 4区 管理学 Q4 MANAGEMENT
R. Allgor, Tolga Çezik, Daniel Chen
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引用次数: 3

Abstract

This paper describes how Amazon redesigned the robotic picking algorithm used in Amazon Robotics (AR) fulfillment centers (FCs) to enable humans and robots to work together effectively. In AR FCs, robotic drives fetch storage pods filled with inventory for associates to pick. The picking algorithm needs to decide which specific units of inventory on which pods should be picked to fulfill customer order shipments. We want to do so in a way that is most efficient and distance traveled by drives per unit picked is the key performance metric. This new algorithm reduced the distance traveled by drives per unit picked by 62% without negative operational impact and has since been implemented in all AR FCs. This improvement reduced the number of drives required in AR FCs by 31%, which amounted to half a billion dollars in savings. The redesigned algorithm enabled seamless collaboration between associates and robots, and its effectiveness in scaling up convinced Amazon to make AR FCs the standard for new FCs, allowing Amazon to reduce the storage footprint by about 29% compared with non-AR FCs. History: This paper was refereed.
亚马逊物流中心的机器人拣选算法使人类和机器人能够有效地协同工作
本文描述了亚马逊如何重新设计亚马逊机器人(AR)履行中心(fc)中使用的机器人拣选算法,以使人类和机器人能够有效地协同工作。在AR FCs中,机器人驱动器会取出装满库存的存储舱,供同事挑选。挑选算法需要决定应该挑选哪些特定的库存单元,以满足客户的订单发货。我们希望以一种最有效的方式做到这一点,并且每个单元驱动器的行驶距离是关键的性能指标。这种新算法在不影响操作的情况下,将每个单元驱动器的行驶距离缩短了62%,并已在所有AR fc中实施。这一改进将AR fc所需的驱动器数量减少了31%,相当于节省了5亿美元。重新设计的算法实现了员工和机器人之间的无缝协作,它在扩大规模方面的有效性说服了亚马逊将AR fc作为新fc的标准,与非AR fc相比,亚马逊可以将存储空间减少约29%。历史:本文被审稿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
21.40%
发文量
51
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