Training Tactile Sensors to Learn Force Sensing from Each Other

Training Tactile Sensors to Learn Force Sensing from Each Other | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Training Tactile Sensors to Learn Force Sensing from Each Other Shan Luo, Zhuo Chen, Ni Ou, Xuyang Zhang, Zhiyuan Wu, Yongqiang Zhao, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6513579/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Humans achieve stable and dexterous object manipulation by coordinating grasp forces across multiple fingers and palms, facilitated by a unified tactile memory system in the somatosensory cortex. This system encodes and stores tactile experiences across skin regions, enabling the flexible reuse and transfer of touch information between fingers and hands. Inspired by this biological capability, we present GenForce, a framework that enables transferable force sensing across tactile sensors in robotic hands. GenForce unifies tactile signals into shared marker representations, analogous to cortical sensory encoding, allowing force prediction models trained on one sensor to be transferred to others without the need for exhaustive force data collection. We demonstrate that GenForce generalizes across both homogeneous sensors with varying configurations and heterogeneous sensors with distinct sensing modalities and material properties. Our results highlight a scalable paradigm for robotic tactile learning, offering new pathways toward adaptable and tactile memory-driven manipulation in unstructured environments. Physical sciences/Engineering/Mechanical engineering Physical sciences/Mathematics and computing/Computer science Full Text Additional Declarations There is NO Competing Interest. Supplementary Files GenForceSupplementary.pdf Supplementary Information VideoS1.mp4 Marker-to-marker translation with simulated data VideoS2.mp4 Marker-to-marker translation in homogeneous translation VideoS3.mp4 Marker-to-marker translation in heterogeneous translation VideoS4.mp4 Real-time force prediction for homogeneous translation VideoS5.mp4 Material compensation performance VideoS6.mp4 Real-time force prediction for heterogeneous translation to uSkin VideoS7.mp4 Real-time force prediction for heterogeneous translation to TacPalm VideoS8.mp4 Real-time force prediction for heterogeneous translation to GelSight Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6513579","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":463077302,"identity":"b9406951-b4e9-4b3f-94f7-b58fd808f566","order_by":0,"name":"Shan Luo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYDACCRBRwMDAz8PAeAAswkOUFgMGBskeBgYStRicIVaL/OzmZw8YDA7LGZ85/OAAQ40dUO8B/FoM7hwzNwBqMTY722ZwgOFYMoPB2QYCWiQSzCSAWhK3necBOoztAIPBeUIOm5H+Daxlcz9Iyz8itDDcyIHYsoG3h+EAY9sBIhx2I6dMIsEg3VjizDGDA4l9yTyShLwPdNg2iQ8V1nL8PckPH3z4ZifHdyaBkMuAIAGJQTAiR8EoGAWjYBQQAQCF40F/5JeAugAAAABJRU5ErkJggg==","orcid":"","institution":"King's College London","correspondingAuthor":true,"prefix":"","firstName":"Shan","middleName":"","lastName":"Luo","suffix":""},{"id":463077303,"identity":"e573043f-ec06-4cc0-97eb-39309647a028","order_by":1,"name":"Zhuo Chen","email":"","orcid":"https://orcid.org/0000-0001-8899-2232","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Zhuo","middleName":"","lastName":"Chen","suffix":""},{"id":463077304,"identity":"1008c3ed-3e0f-427d-a14e-a32c70f39a04","order_by":2,"name":"Ni Ou","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Ni","middleName":"","lastName":"Ou","suffix":""},{"id":463077305,"identity":"491bd308-aa78-427f-b4c7-278ca0107847","order_by":3,"name":"Xuyang Zhang","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Xuyang","middleName":"","lastName":"Zhang","suffix":""},{"id":463077306,"identity":"49ce137b-aa2f-4c5c-9fcb-5e986366d9fa","order_by":4,"name":"Zhiyuan Wu","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Zhiyuan","middleName":"","lastName":"Wu","suffix":""},{"id":463077307,"identity":"42a72ca0-1d02-408e-aaac-d00b51b1fe6b","order_by":5,"name":"Yongqiang Zhao","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Yongqiang","middleName":"","lastName":"Zhao","suffix":""},{"id":463077308,"identity":"e92dfd4d-9cff-4279-91c6-7764f1ac875b","order_by":6,"name":"Yupeng Wang","email":"","orcid":"","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Yupeng","middleName":"","lastName":"Wang","suffix":""},{"id":463077309,"identity":"80fc0285-31c4-43e2-9565-0c5052599c07","order_by":7,"name":"Nathan Lepora","email":"","orcid":"https://orcid.org/0000-0001-5327-1523","institution":"University of Bristol","correspondingAuthor":false,"prefix":"","firstName":"Nathan","middleName":"","lastName":"Lepora","suffix":""},{"id":463077310,"identity":"c78db5c6-6917-41c0-bf84-12518a1a921c","order_by":8,"name":"Lorenzo Jamone","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Lorenzo","middleName":"","lastName":"Jamone","suffix":""},{"id":463077311,"identity":"4ca73a1e-8b60-4e92-af53-dc5630f7fc64","order_by":9,"name":"Jiankang Deng","email":"","orcid":"https://orcid.org/0000-0002-3709-6216","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Jiankang","middleName":"","lastName":"Deng","suffix":""}],"badges":[],"createdAt":"2025-04-23 14:26:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6513579/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6513579/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-026-68753-1","type":"published","date":"2026-01-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":103809856,"identity":"a3f49065-0543-4b33-be09-5c97fc2d8688","added_by":"auto","created_at":"2026-03-03 08:06:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6836725,"visible":true,"origin":"","legend":"Article File","description":"","filename":"GenForceMAIN.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1_covered_090297f8-0891-4b89-bb3a-6e9497b434c4.pdf"},{"id":84415908,"identity":"f2f84897-34e2-4d79-a394-095658398827","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1362968,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"GenForceSupplementary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/9f18d2afb6ac55c30d2908ef.pdf"},{"id":84415909,"identity":"979a04b0-b53c-4d26-8b4d-ec9d1a3caf68","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2042725,"visible":true,"origin":"","legend":"Marker-to-marker translation with simulated data","description":"","filename":"VideoS1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/ddc4fd5da94aac7ee6856b35.mp4"},{"id":84415912,"identity":"4b4540e7-2893-45d4-8421-4b79b50d9d9b","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2731009,"visible":true,"origin":"","legend":"Marker-to-marker translation in homogeneous translation","description":"","filename":"VideoS2.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/d4dd0c7ae4f71137ea3dc705.mp4"},{"id":84415917,"identity":"5b656cc4-4710-43bc-ae8d-aa840f90dc4e","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2837043,"visible":true,"origin":"","legend":"Marker-to-marker translation in heterogeneous translation","description":"","filename":"VideoS3.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/7396d95e1b8ffeb7eab64a5b.mp4"},{"id":84416580,"identity":"ae4b85fa-7de9-48ac-a1ca-230e91147fd9","added_by":"auto","created_at":"2025-06-11 16:44:55","extension":"mp4","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":3404923,"visible":true,"origin":"","legend":"Real-time force prediction for homogeneous translation","description":"","filename":"VideoS4.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/8e041989dd40c71ca186001b.mp4"},{"id":84415915,"identity":"c9ba6a83-199b-45b3-b141-84b1516fea04","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3955114,"visible":true,"origin":"","legend":"\u003cp\u003eMaterial compensation performance\u003c/p\u003e","description":"","filename":"VideoS5.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/070a911e1e36285a00948999.mp4"},{"id":84415914,"identity":"069c07d4-fe6e-4c7b-8f93-22ff28ddf2dc","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2428199,"visible":true,"origin":"","legend":"\u003cp\u003eReal-time force prediction for heterogeneous translation to uSkin\u003c/p\u003e","description":"","filename":"VideoS6.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/773bf6c4d45340dcd0b7be9e.mp4"},{"id":84415919,"identity":"5b5872cb-4cfa-43df-ad15-c670bf10f2bc","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":2527287,"visible":true,"origin":"","legend":"Real-time force prediction for heterogeneous translation to TacPalm","description":"","filename":"VideoS7.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/7ecb7e3fb984271846376f29.mp4"},{"id":84415918,"identity":"d752cf99-01b9-474d-9ed4-14880b50d50c","added_by":"auto","created_at":"2025-06-11 16:36:55","extension":"mp4","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":2538842,"visible":true,"origin":"","legend":"Real-time force prediction for heterogeneous translation to GelSight","description":"","filename":"VideoS8.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6513579/v1/dbbb949acbc4d81bcf2aa387.mp4"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Training Tactile Sensors to Learn Force Sensing from Each Other","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6513579/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6513579/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Humans achieve stable and dexterous object manipulation by coordinating grasp forces across multiple fingers and palms, facilitated by a unified tactile memory system in the somatosensory cortex. This system encodes and stores tactile experiences across skin regions, enabling the flexible reuse and transfer of touch information between fingers and hands. Inspired by this biological capability, we present GenForce, a framework that enables transferable force sensing across tactile sensors in robotic hands. GenForce unifies tactile signals into shared marker representations, analogous to cortical sensory encoding, allowing force prediction models trained on one sensor to be transferred to others without the need for exhaustive force data collection. We demonstrate that GenForce generalizes across both homogeneous sensors with varying configurations and heterogeneous sensors with distinct sensing modalities and material properties. Our results highlight a scalable paradigm for robotic tactile learning, offering new pathways toward adaptable and tactile memory-driven manipulation in unstructured environments.","manuscriptTitle":"Training Tactile Sensors to Learn Force Sensing from Each Other","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-11 16:36:50","doi":"10.21203/rs.3.rs-6513579/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"814af71b-3c04-48d7-ab4d-14d89374e37d","owner":[],"postedDate":"June 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49171099,"name":"Physical sciences/Engineering/Mechanical engineering"},{"id":49171100,"name":"Physical sciences/Mathematics and computing/Computer science"}],"tags":[],"updatedAt":"2026-03-03T08:06:17+00:00","versionOfRecord":{"articleIdentity":"rs-6513579","link":"https://doi.org/10.1038/s41467-026-68753-1","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2026-01-28 05:00:00","publishedOnDateReadable":"January 28th, 2026"},"versionCreatedAt":"2025-06-11 16:36:50","video":"","vorDoi":"10.1038/s41467-026-68753-1","vorDoiUrl":"https://doi.org/10.1038/s41467-026-68753-1","workflowStages":[]},"version":"v1","identity":"rs-6513579","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6513579","identity":"rs-6513579","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}