开发可自适应抓取货架不确定位置物品的机器人系统
An Integrated Approach to Robotic Object Grasping and Manipulation
- 通过自适应策略应对货架中物品位置未知的问题
- 实现无需预知物品位置即可高效抓取指定物品
- 适合自动化仓储、机器人抓取场景的从业者参考
为应对仓库运营中人工劳动强度大、效率低的挑战，亚马逊正大力推动机器人技术应用。尽管已有大量机器人成功部署于仓库内货物运输任务，但从货架上精准抓取物品仍是重大难题。本项目提出一种创新的机器人系统，能够自主完成模拟订单任务，高效从货架上选取特定物品。该系统的突出特点是能应对货架每个隔间中物品位置不确定的挑战。系统设计为可自主调整抓取策略，即使在缺乏物品具体位置先验知识的情况下，仍能有效定位并获取目标物品。
原文摘要 · Abstract (English)
In response to the growing challenges of manual labor and efficiency in warehouse operations, Amazon has embarked on a significant transformation by incorporating robotics to assist with various tasks. While a substantial number of robots have been successfully deployed for tasks such as item transportation within warehouses, the complex process of object picking from shelves remains a significant challenge. This project addresses the issue by developing an innovative robotic system capable of autonomously fulfilling a simulated order by efficiently selecting specific items from shelves. A distinguishing feature of the proposed robotic system is its capacity to navigate the challenge of uncertain object positions within each bin of the shelf. The system is engineered to autonomously adapt its approach, employing strategies that enable it to efficiently locate and retrieve the desired items, even in the absence of pre-established knowledge about their placements.
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