Youcan Yan, Ahmed Zermane, Jia Pan, Abderrahmane Kheddar
{"title":"A soft skin with self-decoupled three-axis force-sensing taxels","authors":"Youcan Yan, Ahmed Zermane, Jia Pan, Abderrahmane Kheddar","doi":"10.1038/s42256-024-00904-9","DOIUrl":null,"url":null,"abstract":"<p>Electronic skins integrating both normal and shear force per taxel have a wide range of applications across diverse fields, including robotics, haptics and health monitoring. Current multi-axis tactile sensors often present complexities in structure and fabrication or require an extensive calibration process, limiting their widespread applications. Here we report an electronic soft magnetic skin capable of self-decoupling three-axis forces at each taxel. We use a simple sensor structure with customizable sensitivity and measurement range, reducing the calibration complexity from known quadratic (<i>N</i><sup>2</sup>) or cubic (<i>N</i><sup>3</sup>) scales down to a linear (3<i>N</i>) scale. The three-axis self-decoupling property of the sensor is achieved by overlaying two sinusoidally magnetized flexible magnetic films with orthogonal magnetization patterns. Leveraging the self-decoupling feature and its simple structure, we demonstrate that our sensor can facilitate a diverse range of applications, such as measuring the three-dimensional force distribution in artificial knee joints, teaching robots by touch demonstration and monitoring the interaction forces between knee braces and human skin during various activities.</p>","PeriodicalId":48533,"journal":{"name":"Nature Machine Intelligence","volume":"13 1","pages":""},"PeriodicalIF":18.8000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Machine Intelligence","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1038/s42256-024-00904-9","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Electronic skins integrating both normal and shear force per taxel have a wide range of applications across diverse fields, including robotics, haptics and health monitoring. Current multi-axis tactile sensors often present complexities in structure and fabrication or require an extensive calibration process, limiting their widespread applications. Here we report an electronic soft magnetic skin capable of self-decoupling three-axis forces at each taxel. We use a simple sensor structure with customizable sensitivity and measurement range, reducing the calibration complexity from known quadratic (N2) or cubic (N3) scales down to a linear (3N) scale. The three-axis self-decoupling property of the sensor is achieved by overlaying two sinusoidally magnetized flexible magnetic films with orthogonal magnetization patterns. Leveraging the self-decoupling feature and its simple structure, we demonstrate that our sensor can facilitate a diverse range of applications, such as measuring the three-dimensional force distribution in artificial knee joints, teaching robots by touch demonstration and monitoring the interaction forces between knee braces and human skin during various activities.
期刊介绍:
Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements.
To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects.
Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.