Universal robotic gripper based on the jamming of granular material

干扰 夹持器 计算机科学 刚度(电磁) 架空(工程) 简单(哲学) 对象(语法) 软件 机械工程 人工智能 模拟 工程类 结构工程 物理 热力学 程序设计语言 操作系统 认识论 哲学
作者
Eric Brown,Nicholas Rodenberg,John R. Amend,Annan Mozeika,E. Steltz,M. R. Zakin,Hod Lipson,Heinrich M. Jaeger
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [Proceedings of the National Academy of Sciences]
卷期号:107 (44): 18809-18814 被引量:1357
标识
DOI:10.1073/pnas.1003250107
摘要

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties remains, however, challenging. Most current designs are based on the multifingered hand, but this approach introduces hardware and software complexities. These include large numbers of controllable joints, the need for force sensing if objects are to be handled securely without crushing them, and the computational overhead to decide how much stress each finger should apply and where. Here we demonstrate a completely different approach to a universal gripper. Individual fingers are replaced by a single mass of granular material that, when pressed onto a target object, flows around it and conforms to its shape. Upon application of a vacuum the granular material contracts and hardens quickly to pinch and hold the object without requiring sensory feedback. We find that volume changes of less than 0.5% suffice to grip objects reliably and hold them with forces exceeding many times their weight. We show that the operating principle is the ability of granular materials to transition between an unjammed, deformable state and a jammed state with solid-like rigidity. We delineate three separate mechanisms, friction, suction, and interlocking, that contribute to the gripping force. Using a simple model we relate each of them to the mechanical strength of the jammed state. This advance opens up new possibilities for the design of simple, yet highly adaptive systems that excel at fast gripping of complex objects.
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