Empowering Particle Jamming Soft Gripper with Tactility via Stretchable Optoelectronic Sensing Skin

IF 6.8 Q1 AUTOMATION & CONTROL SYSTEMS
Liyan Mo, Wenhao Xie, Jingting Qu, Jiutian Xia, Yunquan Li, Yuanfang Zhang, Tao Ren, Yang Yang, Juan Yi, Changchun Wu, Yonghua Chen
{"title":"Empowering Particle Jamming Soft Gripper with Tactility via Stretchable Optoelectronic Sensing Skin","authors":"Liyan Mo,&nbsp;Wenhao Xie,&nbsp;Jingting Qu,&nbsp;Jiutian Xia,&nbsp;Yunquan Li,&nbsp;Yuanfang Zhang,&nbsp;Tao Ren,&nbsp;Yang Yang,&nbsp;Juan Yi,&nbsp;Changchun Wu,&nbsp;Yonghua Chen","doi":"10.1002/aisy.202400285","DOIUrl":null,"url":null,"abstract":"<p>Particle-jamming soft grippers demonstrate notable shape adaptability and adjustable stiffness, which improve their grasping efficiency. However, integrating tactile sensing into these grippers presents challenges due to the specific properties of the particle jamming mechanism. This study introduces a parallel particle jamming soft gripper equipped with tactile sensing capabilities. The gripper consists of two tactile sensing particle jamming pads (TSPJPs) that are integrated with flexible optoelectronic skins. These skins are made of silicone rubber membranes and are embedded with a 3 × 3 array of stretchable optical waveguide arrays (SOWAs). Testing indicates that incorporating these sensors enhances the gripper's tactile sensing capabilities, with minimal impact on its particle jamming-based grasping function. A single TSPJP can accurately detect various contact points and estimate the contract forces. The proposed soft gripper can reliably grasp a wide range of objects, varying in shape, hardness, and weight, and it provides detailed tactile feedback on contact locations and the intensity of the grasping through the SOWA sensor. It can precisely distinguish between different grasping postures using a light gradient boosting machine (LightGBM) learning model. Furthermore, it can effectively detect the slippage of grasped objects, facilitating accurate closed-loop control for secure manipulation.</p>","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 1","pages":""},"PeriodicalIF":6.8000,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400285","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aisy.202400285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Particle-jamming soft grippers demonstrate notable shape adaptability and adjustable stiffness, which improve their grasping efficiency. However, integrating tactile sensing into these grippers presents challenges due to the specific properties of the particle jamming mechanism. This study introduces a parallel particle jamming soft gripper equipped with tactile sensing capabilities. The gripper consists of two tactile sensing particle jamming pads (TSPJPs) that are integrated with flexible optoelectronic skins. These skins are made of silicone rubber membranes and are embedded with a 3 × 3 array of stretchable optical waveguide arrays (SOWAs). Testing indicates that incorporating these sensors enhances the gripper's tactile sensing capabilities, with minimal impact on its particle jamming-based grasping function. A single TSPJP can accurately detect various contact points and estimate the contract forces. The proposed soft gripper can reliably grasp a wide range of objects, varying in shape, hardness, and weight, and it provides detailed tactile feedback on contact locations and the intensity of the grasping through the SOWA sensor. It can precisely distinguish between different grasping postures using a light gradient boosting machine (LightGBM) learning model. Furthermore, it can effectively detect the slippage of grasped objects, facilitating accurate closed-loop control for secure manipulation.

Abstract Image

求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
1.30
自引率
0.00%
发文量
0
审稿时长
4 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信