Flexible Electronic Skin for Monitoring of Grasping State During Robotic Manipulation.

IF 6.4 2区 计算机科学 Q1 ROBOTICS Soft Robotics Pub Date : 2023-04-01 DOI:10.1089/soro.2022.0014
Lusheng Bao, Cheng Han, Guolin Li, Jun Chen, Wenqiang Wang, Hao Yang, Xin Huang, Jiajie Guo, Hao Wu
{"title":"Flexible Electronic Skin for Monitoring of Grasping State During Robotic Manipulation.","authors":"Lusheng Bao,&nbsp;Cheng Han,&nbsp;Guolin Li,&nbsp;Jun Chen,&nbsp;Wenqiang Wang,&nbsp;Hao Yang,&nbsp;Xin Huang,&nbsp;Jiajie Guo,&nbsp;Hao Wu","doi":"10.1089/soro.2022.0014","DOIUrl":null,"url":null,"abstract":"<p><p>Electronic skin for robotic tactile sensing has been studied extensively over the past years, yet practical applications of electronic skin for the grasping state monitoring during robotic manipulation are still limited. In this study, we present the fabrication and implementation of electronic skin sensor arrays for the detection of unstable grasping. The piezoresistive sensor arrays have the advantages of facile fabrication, fast response, and high reliability. With the tactile data from the sensor array, we propose two quantitative indicators, correlation coefficient and wavelet coefficient, to identify grasping with variable forces and slippage. Those two indicators reflect both time and frequency domain characteristics in the contact forces from the sensor array and can be obtained without large amount of calculation. We demonstrate the utility of this method under various conditions, the results indicate grasping with variable forces, and slippage can be distinguished by this method. The flexible sensor arrays are adopted for tactile sensing on a bionic hand, and the effectiveness of this method in detecting various grasping states has been verified. The electronic skin sensor array and the grasping state monitoring method are promising for applications in robotic dexterous manipulation.</p>","PeriodicalId":48685,"journal":{"name":"Soft Robotics","volume":"10 2","pages":"336-344"},"PeriodicalIF":6.4000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Robotics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1089/soro.2022.0014","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 3

Abstract

Electronic skin for robotic tactile sensing has been studied extensively over the past years, yet practical applications of electronic skin for the grasping state monitoring during robotic manipulation are still limited. In this study, we present the fabrication and implementation of electronic skin sensor arrays for the detection of unstable grasping. The piezoresistive sensor arrays have the advantages of facile fabrication, fast response, and high reliability. With the tactile data from the sensor array, we propose two quantitative indicators, correlation coefficient and wavelet coefficient, to identify grasping with variable forces and slippage. Those two indicators reflect both time and frequency domain characteristics in the contact forces from the sensor array and can be obtained without large amount of calculation. We demonstrate the utility of this method under various conditions, the results indicate grasping with variable forces, and slippage can be distinguished by this method. The flexible sensor arrays are adopted for tactile sensing on a bionic hand, and the effectiveness of this method in detecting various grasping states has been verified. The electronic skin sensor array and the grasping state monitoring method are promising for applications in robotic dexterous manipulation.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
柔性电子皮肤在机器人操作过程中的抓取状态监测。
近年来,用于机器人触觉感知的电子皮肤已经得到了广泛的研究,但用于机器人操作过程中抓取状态监测的电子皮肤的实际应用仍然有限。在这项研究中,我们提出了用于检测不稳定抓取的电子皮肤传感器阵列的制造和实现。压阻式传感器阵列具有制作方便、响应速度快、可靠性高等优点。利用传感器阵列的触觉数据,我们提出了相关系数和小波系数两个定量指标来识别变力和滑动抓取。这两个指标反映了传感器阵列接触力的时域和频域特征,无需大量计算即可获得。结果表明,该方法可以在不同的条件下进行抓握,并且可以区分滑移。采用柔性传感器阵列对仿生手进行触觉传感,并验证了该方法检测各种抓取状态的有效性。电子皮肤传感器阵列和抓取状态监测方法在机器人灵巧操作中具有广阔的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Soft Robotics
Soft Robotics ROBOTICS-
CiteScore
15.50
自引率
5.10%
发文量
128
期刊介绍: Soft Robotics (SoRo) stands as a premier robotics journal, showcasing top-tier, peer-reviewed research on the forefront of soft and deformable robotics. Encompassing flexible electronics, materials science, computer science, and biomechanics, it pioneers breakthroughs in robotic technology capable of safe interaction with living systems and navigating complex environments, natural or human-made. With a multidisciplinary approach, SoRo integrates advancements in biomedical engineering, biomechanics, mathematical modeling, biopolymer chemistry, computer science, and tissue engineering, offering comprehensive insights into constructing adaptable devices that can undergo significant changes in shape and size. This transformative technology finds critical applications in surgery, assistive healthcare devices, emergency search and rescue, space instrument repair, mine detection, and beyond.
期刊最新文献
A Biomimetic Adhesive Disc for Robotic Adhesion Sliding Inspired by the Net-Winged Midge Larva. YoMo: Yoshimura Continuum Manipulator for MR Environment. Soft-Rigid Hybrid Revolute and Prismatic Joints Using Multilayered Bellow-Type Soft Pneumatic Actuators: Design, Characterization, and Its Application as Soft-Rigid Hybrid Gripper. Soft Electromagnetic Sliding Actuators for Highly Compliant Planar Motions Using Microfluidic Conductive Coil Array. Thermo-Pneumatic Artificial Muscle: Air-Based Thermo-Pneumatic Artificial Muscles for Pumpless Pneumatic Actuation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1