SSF: Segment Skeleton Filtering Method to Generate a Clean Direction for Automatic Blasting Robots in Shipbuilding

SSF: Segment Skeleton Filtering Method to Generate a Clean Direction for Automatic Blasting Robots in Shipbuilding | 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 Research Article SSF: Segment Skeleton Filtering Method to Generate a Clean Direction for Automatic Blasting Robots in Shipbuilding Jaemin Song, Jaehyun Kim, Seungbeom Seo, Hwa-Jihn Kang, Yu-Cheol Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7830700/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Feb, 2026 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 5 You are reading this latest preprint version Abstract A primary challenge in automating hull plate pretreatment is generating stable driving directions for blasting robots. This study proposes a novel method to generate clean directions for blasting robots, the Segment Skeleton Filtering (SSF). The SSF method uses images collected by combining a camera and a laser-pattern device, consisting of three steps: semantic segmentation, skeletonization, and stable path generation (SPG). First, semantic segmentation employs a laser-pattern device to capture the curved profile features of welding beads and segments overlapping the region between the weld line and the unpretreated region using the early-branched U-Net. Second, skeletonization compresses the segmented region into a center region, reducing the segmentation noise and extracting features that are suitable for center line extraction. Finally, SPG extracts a straight line from this refined region using random sample consensus (RANSAC) and reduces angle variations via a Kalman filter to provide stable driving directions for blasting robots. An experimental validation was conducted using data obtained from the shipbuilding environment. The results demonstrate that the SSF method achieves superior performance concerning segmentation accuracy, robust centerline extraction, and stability in generating driving directions. Automatic blasting robot Semantic segmentation Ship hull pretreatment Skeleton Weld path smoothing Full Text Supplementary Files SSF1.mp4 Cite Share Download PDF Status: Published Journal Publication published 20 Feb, 2026 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Major Revisions Needed 11 Dec, 2025 Reviewers agreed at journal 30 Oct, 2025 Reviewers invited by journal 29 Oct, 2025 Editor assigned by journal 13 Oct, 2025 First submitted to journal 10 Oct, 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-7830700","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":536798014,"identity":"5ecaef8f-e489-4b80-a7ad-a6cb5f121745","order_by":0,"name":"Jaemin Song","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jaemin","middleName":"","lastName":"Song","suffix":""},{"id":536798015,"identity":"8a37a59b-7325-4b94-ad04-09b180132751","order_by":1,"name":"Jaehyun 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