Pose Error Real-Time Prediction and Compensation of a 5-DOF Hybrid Robot Based on Laser Tracker and Externally Mounted Encoders

Pose Error Real-Time Prediction and Compensation of a 5-DOF Hybrid Robot Based on Laser Tracker and Externally Mounted Encoders | 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 Pose Error Real-Time Prediction and Compensation of a 5-DOF Hybrid Robot Based on Laser Tracker and Externally Mounted Encoders Hao Guo, Guangxi Li, Songtao Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6438375/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 7 You are reading this latest preprint version Abstract Error compensation is an effective approach for robots to improve accuracy. This paper presents a novel method to predict and compensate for pose error of a 5-DOF hybrid robot on-line with the usage of externally mounted encoders, concentrating particularly on compensating dynamic errors on the account of changes in external forces or disturbances. A novel method to estimate pose error is proposed employing the offline sampling data from a laser tracker as well as the online measurement data from the external encoders. A real-time procedure for pose error prediction and compensation is applied into the NC system, which involves two successive steps: (1) calculation of pose error based on the online measurement from externally mounted encoders and the offline data measured by the laser tracker employing the moving least squares algorithm, and (2) compensation for the command pose in every interpolation cycle. Experimental verification shows that the residual inaccuracy of pose error prediction is reduced by 61% with respect to that only estimated from offline data under the condition of changing loads and the deviations of predicted errors respect to actual errors are within 5% under a constant load. Physical sciences/Engineering Physical sciences/Engineering/Mechanical engineering Real-time error compensation Hybrid machining robot Laser tracker External metrology systems Moving least square Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 15 May, 2025 Reviews received at journal 04 May, 2025 Reviewers agreed at journal 30 Apr, 2025 Reviewers invited by journal 28 Apr, 2025 Editor assigned by journal 21 Apr, 2025 Submission checks completed at journal 16 Apr, 2025 First submitted to journal 16 Apr, 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. 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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-6438375","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":451722452,"identity":"e6af0e2d-d0b5-4bb3-8c17-0830c6b75032","order_by":0,"name":"Hao Guo","email":"","orcid":"","institution":"Tianjin University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Guo","suffix":""},{"id":451722453,"identity":"45cc6b8f-9bcb-4f8a-95f3-092e73f61028","order_by":1,"name":"Guangxi Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYBACPmYog429wQDCOkBACxtcC88BoJYEYrTAWRIJxGphZ78m8XNHbWKf5OPNr3l/MMjx3Uhg/FyA12E8ZZK9Z44bs0mnlVnzJDAYS95IYJaegV9LmgRv2zE5NukcM2OglsQNNxKAggS0SP5tO8bDJnkGrKWeCC3sx6R522rk2CR4jB8DtSQYEGELs7Vs2wFjNp60MsY5aRKGM888bJbGp4Wf//jDm2/b6hLntx/e/OGNjY083/Hkg5/xaWFg4AFF+mGwjRLA2AHSjA14NTAwsD8AEnUgFvMHAkpHwSgYBaNghAIAqSRBkh+fPy0AAAAASUVORK5CYII=","orcid":"","institution":"Dongguan University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Guangxi","middleName":"","lastName":"Li","suffix":""},{"id":451722454,"identity":"a489d44a-9800-47ee-a353-a7bbedeeeea6","order_by":2,"name":"Songtao Liu","email":"","orcid":"","institution":"Chenxing ( Tianjin) Automation Equipment Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Songtao","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-04-13 09:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6438375/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6438375/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-42162-2","type":"published","date":"2026-04-01T15:59:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":106343781,"identity":"84dfe587-a901-4c65-852d-fbe44ff95a80","added_by":"auto","created_at":"2026-04-07 16:09:15","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5152995,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptrevised.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6438375/v1_covered_720f7043-a966-475f-8141-568b65d2fdcc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pose Error Real-Time Prediction and Compensation of a 5-DOF Hybrid Robot Based on Laser Tracker and Externally Mounted Encoders","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"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":"Real-time error compensation, Hybrid machining robot, Laser tracker, External metrology systems, Moving least square","lastPublishedDoi":"10.21203/rs.3.rs-6438375/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6438375/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eError compensation is an effective approach for robots to improve accuracy. This paper presents a novel method to predict and compensate for pose error of a 5-DOF hybrid robot on-line with the usage of externally mounted encoders, concentrating particularly on compensating dynamic errors on the account of changes in external forces or disturbances. A novel method to estimate pose error is proposed employing the offline sampling data from a laser tracker as well as the online measurement data from the external encoders. A real-time procedure for pose error prediction and compensation is applied into the NC system, which involves two successive steps: (1) calculation of pose error based on the online measurement from externally mounted encoders and the offline data measured by the laser tracker employing the moving least squares algorithm, and (2) compensation for the command pose in every interpolation cycle. 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