Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106364
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dc.contributorDepartment of Mechanical Engineering-
dc.creatorPeng, Ren_US
dc.creatorNavarro-Alarcon, Den_US
dc.creatorWu, Ven_US
dc.creatorYang, Wen_US
dc.date.accessioned2024-05-09T00:53:01Z-
dc.date.available2024-05-09T00:53:01Z-
dc.identifier.isbn978-1-7281-5716-0 (Print on Demand(PoD))en_US
dc.identifier.isbn978-1-7281-5715-3 (Electronic)en_US
dc.identifier.isbn978-1-7281-5714-6 (USB)en_US
dc.identifier.urihttp://hdl.handle.net/10397/106364-
dc.description2020 17th International Conference on Ubiquitous Robots (UR 2020), Kyoto, Japan, 22-26 June 2020en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication R. Peng, D. Navarro-Alarcon, V. Wu and W. Yang, "A Point Cloud-Based Method for Automatic Groove Detection and Trajectory Generation of Robotic Arc Welding Tasks," 2020 17th International Conference on Ubiquitous Robots (UR), Kyoto, Japan, 2020, pp. 380-386 is available at https://doi.org/10.1109/UR49135.2020.9144861.en_US
dc.titleA point cloud-based method for automatic groove detection and trajectory generation of robotic arc welding tasksen_US
dc.typeConference Paperen_US
dc.identifier.spage380en_US
dc.identifier.epage386en_US
dc.identifier.doi10.1109/UR49135.2020.9144861en_US
dcterms.abstractIn this paper, in order to pursue high-efficiency robotic arc welding tasks, we propose a method based on point cloud acquired by an RGB-D sensor. The method consists of two parts: welding groove detection and 3D welding trajectory generation. The actual welding scene could be displayed in 3D point cloud format. Focusing on the geometric feature of the welding groove, the detection algorithm is capable of adapting well to different welding workpieces with a V-type welding groove. Meanwhile, a 3D welding trajectory involving 6-DOF poses of the welding groove for robotic manipulator motion is generated. With an acceptable error in trajectory generation, the robotic manipulator could drive the welding torch to follow the trajectory and execute welding tasks. In this paper, details of the integrated robotic system are also presented. Experimental results prove application value of the presented welding robotic system.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2020 17th International Conference on Ubiquitous Robots (UR 2020), Kyoto, Japan, 22-26 June 2020, p. 380-386en_US
dcterms.issued2020-
dc.identifier.scopus2-s2.0-85094315905-
dc.relation.conferenceUbiquitous Robots [UR]-
dc.description.validate202405 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberME-0253-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextChinese National Engineering Research Centre for Steel Construction (Hong Kong Branch) at The Hong Kong Polytechnic University; The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS21550886-
dc.description.oaCategoryGreen (AAM)en_US
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