Fast three-dimensional point cloud registration algorithm based on plane and curvature parameters

Fast three-dimensional point cloud registration algorithm based on plane and curvature parameters | 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 Fast three-dimensional point cloud registration algorithm based on plane and curvature parameters Zhengguang Duan, Jiabin Liu, Shenyuan Ye, Wangyang Lou, Yuanqing Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7815422/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The rapid generation of three-dimensional (3D) imaging has improved the safety and operational efficiency of advanced driver assistance systems and mobile robotics technologies. To expedite the stitching process for 3D point cloud data, this study proposes and validates a method that combines coarse registration based on planarity and fine registration based on curvature features. Experimental results demonstrated that compared to the iterative closest point algorithm, the proposed algorithm achieves a faster registration speed, improved by 19.7%, and higher efficiency without compromising the matching residuals. Processing point cloud data without planar information posed challenges in terms of efficiency; however, a notable improvement in processing speed was observed, with point cloud data containing planar scenes. It is important for applications related to 3D imaging registration. Physical sciences/Engineering Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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-7815422","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":538398881,"identity":"cf5ab6a0-46a6-40bc-98d6-9df2b7f54b14","order_by":0,"name":"Zhengguang Duan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDCCA0D8weA/Dz8z8+EHRGthnFHBLCPZzpZmQLQWZp4zzDYG53kUJIjSwXcj+dkD3jY2HuPDPAwGDDU20QS1SN5IMzeQbOPhMTvMe+ABw7G03AZCWgxuJJhJGLZJALXwJRgwNhwmRkv6N4nENgMe42YeAwkiteSYSRw4k8BjwEysFskzb8okGyoO8EgcBgZyAjF+4Tuevk36j8EBe/7+w4cffKixIawFFSSQpnwUjIJRMApGAS4AAMTzPgVLW1RxAAAAAElFTkSuQmCC","orcid":"","institution":"Nanjing University","correspondingAuthor":true,"prefix":"","firstName":"Zhengguang","middleName":"","lastName":"Duan","suffix":""},{"id":538398882,"identity":"23533cdb-fdb3-4143-a195-16b83ece6eb9","order_by":1,"name":"Jiabin Liu","email":"","orcid":"","institution":"Nanjing University","correspondingAuthor":false,"prefix":"","firstName":"Jiabin","middleName":"","lastName":"Liu","suffix":""},{"id":538398883,"identity":"dcb76e10-6f7f-41fd-82d6-ec23787cb525","order_by":2,"name":"Shenyuan Ye","email":"","orcid":"","institution":"Nanjing University","correspondingAuthor":false,"prefix":"","firstName":"Shenyuan","middleName":"","lastName":"Ye","suffix":""},{"id":538398884,"identity":"fb9bf833-8ac8-4e1a-ac95-7ad09f192922","order_by":3,"name":"Wangyang Lou","email":"","orcid":"","institution":"Hangzhou Innovation Institute of Beihang University","correspondingAuthor":false,"prefix":"","firstName":"Wangyang","middleName":"","lastName":"Lou","suffix":""},{"id":538398888,"identity":"e2d97c6a-637f-401a-94c9-da7bfbb5570b","order_by":4,"name":"Yuanqing Wang","email":"","orcid":"","institution":"Nanjing University","correspondingAuthor":false,"prefix":"","firstName":"Yuanqing","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-10-09 09:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7815422/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7815422/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94948494,"identity":"c7d9331d-1c18-4e44-99b9-3d2b8cbd6cd5","added_by":"auto","created_at":"2025-11-02 10:59:15","extension":"json","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5854,"visible":true,"origin":"","legend":"","description":"","filename":"841e3d7a15144966aca53873cfdcffc8.json","url":"https://assets-eu.researchsquare.com/files/rs-7815422/v1/d7094dfb1608e49baee74d0b.json"},{"id":96048541,"identity":"983089c2-0a13-477a-b77d-a1ab9196351f","added_by":"auto","created_at":"2025-11-17 06:24:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1493219,"visible":true,"origin":"","legend":"","description":"","filename":"ScientificReports1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7815422/v1_covered_580f37c9-b817-427b-ace7-0c6584a76169.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fast three-dimensional point cloud registration algorithm based on plane and curvature parameters","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7815422/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7815422/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The rapid generation of three-dimensional (3D) imaging has improved the safety and operational efficiency of advanced driver assistance systems and mobile robotics technologies. 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