用双手非抓取方式在杂乱货架上捡起难抓物品，成功率超6成。
In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation
- 通过双臂接触推动清除遮挡，实现对不可抓物体的非握取搬运。
- 无硬件改动下，杂乱场景成功率达67%，未见物品也能成功拾取。
- 适合真实超市环境中的复杂物品搬运，无需额外机械改造。
在真实世界中抓取多样物品是机器人的一项基础技能。然而，许多现实场景中的物体体积大、重量重或形状不规则，难以被传统末端执行器如吸盘和平行爪夹持器（PJG）抓取。本文提出一种无需硬件改造的双臂非抓取操作方法，扩展了可拾取物品范围。研究聚焦于超市购物场景，使用配备吸盘和PJG的双臂移动操作机器人，从紧密排列的货架上取回无法抓握的物品。基于视觉观测，算法首先依据力闭合与摩擦约束识别最优抓点；若抓点被遮挡，则执行一系列非抓取推移动作以清除障碍。随后，利用末端执行器侧面接触实现双臂抓取。在模拟超市环境中，102次无杂乱场景试验成功率达90%；45次有杂乱场景试验成功率为67%。系统还部署于真实超市，成功拾取此前未见过的物品。结果表明，双臂非抓取操作在真实世界机器人拣选任务中具有巨大潜力。视频演示见 youtu.be/g0hOrDuK8jM。
原文摘要 · Abstract (English)
Picking diverse objects in the real world is a fundamental robotics skill. However, many objects in such settings are bulky, heavy, or irregularly shaped, making them ungraspable by conventional end effectors like suction grippers and parallel jaw grippers (PJGs). In this paper, we expand the range of pickable items without hardware modifications using bimanual nonprehensile manipulation. We focus on a grocery shopping scenario, where a bimanual mobile manipulator equipped with a suction gripper and a PJG is tasked with retrieving ungraspable items from tightly packed grocery shelves. From visual observations, our method first identifies optimal grasp points based on force closure and friction constraints. If the grasp points are occluded, a series of nonprehensile nudging motions are performed to clear the obstruction. A bimanual grasp utilizing contacts on the side of the end effectors is then executed to grasp the target item. In our replica grocery store, we achieved a 90% success rate over 102 trials in uncluttered scenes, and a 67% success rate over 45 trials in cluttered scenes. We also deployed our system to a real-world grocery store and successfully picked previously unseen items. Our results highlight the potential of bimanual nonprehensile manipulation for in-the-wild robotic picking tasks. A video summarizing this work can be found at youtu.be/g0hOrDuK8jM
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