A point cloud-based welding trajectory planning method for plane welds

A point cloud-based welding trajectory planning method for plane welds | 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 A point cloud-based welding trajectory planning method for plane welds Yuankai Zhang, Yong Jiang, Xincheng Tian, Xiaolong Xu, Yusen Geng, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1908430/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Jan, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 5 You are reading this latest preprint version Abstract Plane welds are a common type of weld in industrial sites. When the welding robot welds multiple types of plane welds at the same time, the traditional teaching and programming modes become relatively complicated. Therefore, in order to solve the problem of automatic robot welding of various types of plane welds, taking plane V-type butt, plane I-type butt, and plane lap welds as examples, this paper proposes a plane weld extraction method based on 3D vision. Firstly, in order to realize the line and plane segmentation of the workpiece point cloud, we establish the concept of plane point cloud density. Secondly, to segment workpiece edge lines, an iterative segmentation algorithm based on RANSAC is proposed. Then, based on the geometric features of the workpiece, a method for extracting weld feature points based on centroid positioning is proposed. Finally, the least squares method is used to fit the feature points of the welding seam to complete the welding trajectory planning. The experimental results show that the method can well solve the problem of automatic planning welding trajectory of plane V-type butt, plane I-type butt, and plane lap welds, to realize that the welding robot can simultaneously weld various plane welds without teaching and programming. 3D vision Weld seam extraction Point cloud feature extraction Without teaching and programming Welding path planning Full Text Cite Share Download PDF Status: Published Journal Publication published 12 Jan, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Minor Revisions Needed 28 Nov, 2022 Reviewers agreed at journal 09 Aug, 2022 Reviewers invited by journal 02 Aug, 2022 Editor assigned by journal 01 Aug, 2022 First submitted to journal 29 Jul, 2022 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. 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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-1908430","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":125749057,"identity":"cc885230-105a-4cbe-a036-b48d8367b431","order_by":0,"name":"Yuankai Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuankai","middleName":"","lastName":"Zhang","suffix":""},{"id":125749058,"identity":"712f3edf-63dd-493b-aba3-793f21352845","order_by":1,"name":"Yong 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