用电永磁体干扰金属板的刚度调制

IF 4.6 2区 计算机科学 Q2 ROBOTICS
Leah T. Gaeta;Vi T. Vo;Sang-Yoep Lee;Srushti Raste;Megha Venkatesam;Jacob Rogatinsky;M. Deniz Albayrak;Tommaso Ranzani
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引用次数: 0

摘要

软机器人表现出自然的顺应性,这在许多应用中是可取的,但当需要更多的刚度时,通常需要刚度调制技术。然而,许多现有的加固技术缺乏可移植性或快速响应时间,阻碍了软机器人的普遍采用。本文介绍了一种新的基于磁的快速刚度调制方法,该方法由于电子控制而具有可移植性。这种技术将固有磁性金属薄片的薄层与电永磁体(epm)产生的磁场结合在一起,产生快速的刚度变化。介绍了具有不同层数的样品的准静态和动态力学特性,强调了如何利用epm产生的磁力来产生干扰效果。在准静态和动态表征期间,刚度增加了68%,能量吸收高达113 mJ。最后,我们演示了这种干扰技术如何在触觉反馈应用中使用,并玩了一个小型版的游戏。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Jamming Metal Sheets Using Electropermanent Magnets for Stiffness Modulation
Soft robots exhibit natural compliance which is desirable in many applications, but often require stiffness modulation techniques when more rigidity is needed. However, many existing stiffening techniques lack portability or fast response times, hindering the ubiquitous adoption of soft robots. Here we introduce a new rapid stiffness modulation method based on magnetism that exhibits portability due to electronic control. This technique jams together thin layers of inherently magnetic metal sheets with a magnetic field generated by electropermanent magnets (EPMs), producing rapid stiffness changes. Quasi-static and dynamic mechanical characterizations for samples with varied layer numbers are presented, highlighting how the magnetic attraction generated by EPMs can be exploited to create a jamming effect. Stiffness increases of up to 68% and energy absorptions of up to 113 mJ were found during quasi-static and dynamic characterizations, respectively. Finally, we demonstrate how this jamming technique can be used in a haptic feedback application and to play a miniaturized version of the game of Skee-Ball.
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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