Automating warehouse operations can reduce logistics overhead costs, ultimately driving down the final price for consumers, increasing the speed of delivery, and enhancing the resiliency to market fluctuations. This extended abstract showcases a large-scale package manipulation from unstructured piles in Amazon Robotics' Robot Induction (Robin) fleet, which is used for picking and singulating up to 6 million packages per day and so far has manipulated over 2 billion packages. It describes the various heuristic methods developed over time and their successor, which utilizes a pick success predictor trained on real production data. To the best of the authors' knowledge, this work is the first large-scale deployment of learned pick quality estimation methods in a real production system.

翻译：自动化仓储作业能够降低物流管理费用，进而降低终端消费者价格、提高配送速度，并增强对市场波动的适应能力。本文简要展示亚马逊机器人公司感应入库（Robin）车队对非结构化堆叠包裹的大规模拾取操作——该车队每日完成多达600万件的包裹拾取与分离操作，迄今已处理超过20亿件包裹。文中详述了历史上开发的各种启发式方法及其后继方案，该方案利用基于真实生产数据训练的拾取成功率预测器。据作者所知，本工作首次将基于学习的拾取质量评估方法大规模部署至实际生产系统。