Evaluating FoundationPose Object Registration Accuracy for AR-Guided Industrial Inspection

Evaluating FoundationPose Object Registration Accuracy for AR-Guided Industrial Inspection | 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 Evaluating FoundationPose Object Registration Accuracy for AR-Guided Industrial Inspection Christian Masuhr, Julian Koch, Tim Oels, Thorsten Schüppstuhl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7992985/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Augmented Reality (AR) can enhance industrial processes like manual inspections by increasing safety and efficiency. This isachieved by superimposing virtual guidance directly onto the physical environment, such as visual highlights, step-by-stepinstructions, or animated tool paths. The accurate alignment of virtual guidance depends directly on the precise registration ofreal-world components. This study evaluates the 6D pose estimation accuracy of the FoundationPose framework for registeringreal-world, complex industrial components (e.g., fittings, flanges) from a single RGB-D image without object-specific retraining.Our evaluation demonstrates robust performance that meets the requirements for AR assisted inspection, achieving mediantranslational deviations between 0.6 mm and 2.8 mm and a median rotational error of approximately 2.8° for plane-symmetriccomponents. While performance remained stable against partial occlusions and reflective surfaces, the results highlight thataccuracy is limited by key challenges, including performance degradation with symmetric and texture-poor objects and theneed for optimization for real-time mobile deployment. Despite these limitations, the high baseline accuracy identified in thisstudy validates the significant potential of FoundationPose for industrial AR applications that demand precise alignment ofvirtual overlays. Physical sciences/Engineering Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 Apr, 2026 Reviewers agreed at journal 11 Apr, 2026 Reviewers invited by journal 02 Mar, 2026 Editor assigned by journal 25 Feb, 2026 Editor invited by journal 06 Nov, 2025 Submission checks completed at journal 04 Nov, 2025 First submitted to journal 04 Nov, 2025 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-7992985","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":540135886,"identity":"583074f0-23f7-4fbf-b5b7-f0ca5dad30c2","order_by":0,"name":"Christian Masuhr","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIie3RP0sDMRjH8V856GLCrZGAfQspB9eWq/hWcgjXUafipAUhk90LvomDg4NuKYHr5qxQEBHcu91thh74Z0jP0SHfIZDhw/OEAD7ff4wB+nC2aYRAPwCCDiJ/kFP1BwLIr6uGqDpI+Lh82zT1eDDCSbpv1O4qen2I36+RnDmH7LbCEMmG6wUtOFUfk7Iio2iFWeQigmUw9i29XNOc95QRcUViTmDSxRGyqSW7sKRoGksi1ZK7Y0TbxVJLSkYtEf2WSIcAe7aLkYxd5oaWCXkyglXZnBMxG7qmhKss2NfT2/N8uyxe6rkR4b0pOblJBq4p3/3+CNENfD6fz+fuEzP+UcqrOhqRAAAAAElFTkSuQmCC","orcid":"","institution":"Hamburg University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Christian","middleName":"","lastName":"Masuhr","suffix":""},{"id":540135891,"identity":"23d55b1c-b8ce-42c1-8d90-c5f55e33c3ba","order_by":1,"name":"Julian Koch","email":"","orcid":"","institution":"Hamburg University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"","lastName":"Koch","suffix":""},{"id":540135892,"identity":"1c094525-e397-4c65-816a-e429900cc3a5","order_by":2,"name":"Tim Oels","email":"","orcid":"","institution":"Hamburg University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"","lastName":"Oels","suffix":""},{"id":540135895,"identity":"ae383502-49ac-483a-84a9-d57b90a624a6","order_by":3,"name":"Thorsten Schüppstuhl","email":"","orcid":"","institution":"Hamburg University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Thorsten","middleName":"","lastName":"Schüppstuhl","suffix":""}],"badges":[],"createdAt":"2025-10-30 23:23:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7992985/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7992985/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95313720,"identity":"d5c0e095-848b-4cfc-bf08-ea6885a637a7","added_by":"auto","created_at":"2025-11-06 15:51:55","extension":"json","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6089,"visible":true,"origin":"","legend":"","description":"","filename":"7c16f518a0084647a9a2510ff2e4b4ca.json","url":"https://assets-eu.researchsquare.com/files/rs-7992985/v1/fb8aefff41c8747daeb78edb.json"},{"id":95315699,"identity":"0761e536-aecd-448a-b518-957c20461d31","added_by":"auto","created_at":"2025-11-06 15:56:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3205885,"visible":true,"origin":"","legend":"","description":"","filename":"NatureSRTUHHV4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7992985/v1_covered_7cb7b017-ebdd-40b2-9d9c-3f1bf50ebe11.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating FoundationPose Object Registration Accuracy for AR-Guided Industrial Inspection","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7992985/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7992985/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Augmented Reality (AR) can enhance industrial processes like manual inspections by increasing safety and efficiency. This isachieved by superimposing virtual guidance directly onto the physical environment, such as visual highlights, step-by-stepinstructions, or animated tool paths. The accurate alignment of virtual guidance depends directly on the precise registration ofreal-world components. This study evaluates the 6D pose estimation accuracy of the FoundationPose framework for registeringreal-world, complex industrial components (e.g., fittings, flanges) from a single RGB-D image without object-specific retraining.Our evaluation demonstrates robust performance that meets the requirements for AR assisted inspection, achieving mediantranslational deviations between 0.6 mm and 2.8 mm and a median rotational error of approximately 2.8° for plane-symmetriccomponents. While performance remained stable against partial occlusions and reflective surfaces, the results highlight thataccuracy is limited by key challenges, including performance degradation with symmetric and texture-poor objects and theneed for optimization for real-time mobile deployment. Despite these limitations, the high baseline accuracy identified in thisstudy validates the significant potential of FoundationPose for industrial AR applications that demand precise alignment ofvirtual overlays.","manuscriptTitle":"Evaluating FoundationPose Object Registration Accuracy for AR-Guided Industrial Inspection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 05:25:36","doi":"10.21203/rs.3.rs-7992985/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-17T11:51:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115697413030687668853049849949385996723","date":"2026-04-11T06:28:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-02T08:17:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-25T05:58:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-06T15:53:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-04T18:56:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-11-04T18:55:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1fd2ece8-bbab-418f-8fe1-04c709d3763c","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":57454524,"name":"Physical sciences/Engineering"},{"id":57454525,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2026-03-02T08:24:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 05:25:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7992985","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7992985","identity":"rs-7992985","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}