Pushing the Boundaries of Robotic Computed Tomography: Automated Twin-Robot CT Scan with Maximum Reachability

Pushing the Boundaries of Robotic Computed Tomography: Automated Twin-Robot CT Scan with Maximum Reachability | 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 Pushing the Boundaries of Robotic Computed Tomography: Automated Twin-Robot CT Scan with Maximum Reachability Jonas Schnitzer, Vinayaka Raju Sathyanarayana Raju, Nihat Emir Erdebil, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9280493/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract Computed tomography is a widely used imaging method for non-destructive testing. However, standard CT systems face fundamental limitations when scanning large objects such as car bodies, which must fit between the X-ray source and detector, both of which need freedom of movement around the specimen. Twin-robotic CT systems with high degrees of freedom address these limitations by enabling free positioning of the X-ray source and detector in space, making non-destructive CT testing of large objects feasible. However, achieving collision-free positioning of the robots is a challenging problem that is often neglected in theoretical representations of twin-robot CT configurations. This paper presents a systematic methodology for performing region-of-interest scans on large objects. The approach exploits the test object's geometry to determine robot reachability, which serves as the foundation for trajectory planning by incorporating accessible regions. By leveraging both rotational and translational degrees of freedom, including variable source-detector distances and detector rotations, the methodology expands the range of collision-free poses, thereby increasing reachability and enabling more flexible trajectory design. The methodology is modular and adapts to arbitrary system configurations and test samples via cad-based geometry definition, where the test object determines the collision-free workspace. It is demonstrated on a BMW 4-series body-in-white through comprehensive batch simulation across 273 roi positions, evaluating reachability improvements achieved through the introduced degrees of freedom using a data completeness trajectory optimization criterion. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 11 May, 2026 Reviews received at journal 08 May, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 08 Apr, 2026 Editor invited by journal 07 Apr, 2026 Submission checks completed at journal 04 Apr, 2026 First submitted to journal 04 Apr, 2026 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. 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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-9280493","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":619536222,"identity":"c964470e-c1eb-4e30-b1ba-be4e2c7c6255","order_by":0,"name":"Jonas Schnitzer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIie3RMUvEMBTA8XccNMtDcEupNF8hR6A39D5MDsEuQdeb7rrdUnGN3+aOwE3RWemiOLg4nFvEQdP2QBwigotD/kvh0R8vJACx2D+M1P3HAKsRQPajq71BGAfJaCDPwDcd6Qza0dMvyAdw8KRfQ9VY/EjWl9tXBy1wcrN7eHTLfHr9kmQIZR4kze2p/6EF1pxXXMpEnLQXOz+pRJBoxTPwBO6woFLiXGeq22LmdZiIN+dv7EDoSqeWvHuyCpFjrQqKX4RLSrHfIkMHy9AWJXKD3Horz+REo0pSzatJaMsRacS9W5icrW2RutmSUWITul+ULLRlaHiU75NYLBaL/aFPh65MoX3SOsYAAAAASUVORK5CYII=","orcid":"","institution":"University of Erlangen-Nuremberg","correspondingAuthor":true,"prefix":"","firstName":"Jonas","middleName":"","lastName":"Schnitzer","suffix":""},{"id":619536226,"identity":"e4afc6c2-8440-44c7-9d76-f9d6a27ca12e","order_by":1,"name":"Vinayaka Raju Sathyanarayana Raju","email":"","orcid":"","institution":"TU Dortmund University","correspondingAuthor":false,"prefix":"","firstName":"Vinayaka","middleName":"Raju Sathyanarayana","lastName":"Raju","suffix":""},{"id":619536228,"identity":"88a2c885-2aaa-4c11-9fac-24f39e0ed6f5","order_by":2,"name":"Nihat Emir Erdebil","email":"","orcid":"","institution":"Technical University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Nihat","middleName":"Emir","lastName":"Erdebil","suffix":""},{"id":619536229,"identity":"1179f00d-8ba1-427a-a4c4-6b8208754837","order_by":3,"name":"Gabriel Herl","email":"","orcid":"","institution":"Deggendorf Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"","lastName":"Herl","suffix":""},{"id":619536230,"identity":"0a603ede-d4c8-40fc-ac86-edfab144f4e5","order_by":4,"name":"Andreas Maier","email":"","orcid":"","institution":"University of Erlangen-Nuremberg","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Maier","suffix":""}],"badges":[],"createdAt":"2026-03-31 13:25:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9280493/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9280493/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106941648,"identity":"8fea20e5-fcf1-4e1e-8fcb-f94222e82b18","added_by":"auto","created_at":"2026-04-15 05:34:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2111382,"visible":true,"origin":"","legend":"","description":"","filename":"AScanwithMaximalReachability02.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9280493/v1_covered_f40c0476-be51-4009-85d2-2e232ce29f04.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pushing the Boundaries of Robotic Computed Tomography: Automated Twin-Robot CT Scan with Maximum Reachability","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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-9280493/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9280493/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Computed tomography is a widely used imaging method for non-destructive testing. 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