RISO: Combining Rigid Grippers with Soft Switchable Adhesives
RISO: Combining Rigid Grippers with Soft Switchable Adhesives
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DOI：
10.1109/robosoft55895.2023.10122030
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发表时间：
2022-10
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影响因子：
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通讯作者：
Shaunak A. Mehta;Yeunhee Kim;Joshua Hoegerman;Michael D. Bartlett;Dylan P. Losey
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作者：
Shaunak A. Mehta;Yeunhee Kim;Joshua Hoegerman;Michael D. Bartlett;Dylan P. Losey
协助人类的机器人手臂应该能够拾取、移动和释放日常物体。如今的辅助机器人手臂使用刚性夹具来将物品夹在手指之间。虽然这些刚性夹具非常适合抓取大型和重型物体，但它们通常难以抓取小型、大量或精致的物体（例如食物）。软夹具涵盖了光谱的另一端；这些夹具使用粘合剂或改变形状来包裹小型和不规则的物品，但无法施加操纵重物所需的巨大力量。在本文中，我们介绍了 RIgid-SOft (RISO) 夹具，它将可切换的软粘合剂与标准刚性机构相结合，以实现各种机器人抓取。我们利用新型软材料开发 RISO 夹具，该材料通过气动控制形状和刚度调节来实时改变粘附力。通过将这些软粘合剂安装在刚性手指的底部，我们创建了一个可以使用纯刚性抓握（捏住物体）或纯软抓握（粘附到物体）与物体交互的夹具。这种能力的增强需要额外的决策，因此我们制定了一种共享控制方法，可以部分自动化机器人手臂的运动。在实践中，该控制器会对齐 RISO 夹具，同时推断人类想要抓取哪个物体以及人类想要如何抓取该物体。我们的用户研究表明，RISO 抓取器可以从现有数据集中拾取、移动和释放家居用品，并且当人类和机器人之间共享控制时，系统可以更成功、更高效地执行抓取操作。请在此处观看视频：https://youtu.be/5uLUkBYcnwg。
Robot arms that assist humans should be able to pick up, move, and release everyday objects. Today's assistive robot arms use rigid grippers to pinch items between fingers; while these rigid grippers are well suited for large and heavy objects, they often struggle to grasp small, numerous, or delicate items (such as foods). Soft grippers cover the opposite end of the spectrum; these grippers use adhesives or change shape to wrap around small and irregular items, but cannot exert the large forces needed to manipulate heavy objects. In this paper we introduce RIgid-SOft (RISO) grippers that combine switchable soft adhesives with standard rigid mechanisms to enable a diverse range of robotic grasping. We develop RISO grippers by leveraging a novel class of soft materials that change adhesion force in real-time through pneumatically controlled shape and rigidity tuning. By mounting these soft adhesives on the bottom of rigid fingers, we create a gripper that can interact with objects using either purely rigid grasps (pinching the object) or purely soft grasps (adhering to the object). This increased capability requires additional decision making, and we therefore formulate a shared control approach that partially automates the motion of the robot arm. In practice, this controller aligns the RISO gripper while inferring which object the human wants to grasp and how the human wants to grasp that item. Our user study demonstrates that RISO grippers can pick up, move, and release household items from existing datasets, and that the system performs grasps more successfully and efficiently when sharing control between the human and robot. See videos here: https://youtu.be/5uLUkBYcnwg.