High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor
With the rapid development of artificial intelligence and computer vision, numerous technologies have been introduced to automate manufacturing in the industry. Typical metal workpieces in the industry often have highly reflective surfaces, come in various sizes, and are positioned irregularly. The...
Gespeichert in:
| Veröffentlicht in: | Machine vision and applications 2024-11, Vol.35 (6), p.132, Article 132 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 6 |
| container_start_page | 132 |
| container_title | Machine vision and applications |
| container_volume | 35 |
| creator | Liang, Jixin Ye, Yuping Wu, Di Chen, Siyuan Song, Zhan |
| description | With the rapid development of artificial intelligence and computer vision, numerous technologies have been introduced to automate manufacturing in the industry. Typical metal workpieces in the industry often have highly reflective surfaces, come in various sizes, and are positioned irregularly. The motor rotor presented in this paper is one such representative workpiece. Traditional grasping methods for workpiece loading and unloading are pre-programmed and often struggle to cope with complex and disordered situations. In this paper, we introduce a structured light (SL) sensor as the visual guide for the triaxial robot. Furthermore, we propose a high-precision hand-eye calibration method for the non-orthogonal coordinate system of the triaxial robot. Additionally, a motor rotor center localization method based on U-Net image segmentation is proposed. By combining the high-precision hand-eye calibration and localization, we can accurately and automatically locate and grasp the rotor. We have conducted sufficient experiments to verify the effectiveness and accuracy of our system. |
| doi_str_mv | 10.1007/s00138-024-01610-7 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3112646053</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3112646053</sourcerecordid><originalsourceid>FETCH-LOGICAL-c200t-56a50042101a13736ea1dc03e4efe0f5b67cdcd0878350e64de9ac6fa00508983</originalsourceid><addsrcrecordid>eNp9kE9LAzEQxYMoWKtfwFPAc3Sy2U12j1L_VCh40XNIs8m6pbupmSzYb29qBW9eZgbmvd8Mj5BrDrccQN0hABc1g6JkwCUHpk7IjJeiYFzJ5pTMoMlzDU1xTi4QNwBQKlXOyGbZdx_Med_b3o12T82UwmCSa2mKvfnqzZbGsA6JdtHgrh87intMbqA-RDqElGs8VKQTHrbigWKKk01TzIxtpieKbsQQL8mZN1t0V799Tt6fHt8WS7Z6fX5Z3K-YLQASq6Sp8ncFB264UEI6w1sLwpXOO_DVWirb2hZqVYsKnCxb1xgrvQGooG5qMSc3R-4uhs_JYdKbMMUxn9SC80KWEiqRVcVRZWNAjM7rXewHE_eagz5kqo-Z6pyp_slUq2wSRxNm8di5-If-x_UN-OR6_g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3112646053</pqid></control><display><type>article</type><title>High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor</title><source>Springer Nature - Complete Springer Journals</source><creator>Liang, Jixin ; Ye, Yuping ; Wu, Di ; Chen, Siyuan ; Song, Zhan</creator><creatorcontrib>Liang, Jixin ; Ye, Yuping ; Wu, Di ; Chen, Siyuan ; Song, Zhan</creatorcontrib><description>With the rapid development of artificial intelligence and computer vision, numerous technologies have been introduced to automate manufacturing in the industry. Typical metal workpieces in the industry often have highly reflective surfaces, come in various sizes, and are positioned irregularly. The motor rotor presented in this paper is one such representative workpiece. Traditional grasping methods for workpiece loading and unloading are pre-programmed and often struggle to cope with complex and disordered situations. In this paper, we introduce a structured light (SL) sensor as the visual guide for the triaxial robot. Furthermore, we propose a high-precision hand-eye calibration method for the non-orthogonal coordinate system of the triaxial robot. Additionally, a motor rotor center localization method based on U-Net image segmentation is proposed. By combining the high-precision hand-eye calibration and localization, we can accurately and automatically locate and grasp the rotor. We have conducted sufficient experiments to verify the effectiveness and accuracy of our system.</description><identifier>ISSN: 0932-8092</identifier><identifier>EISSN: 1432-1769</identifier><identifier>DOI: 10.1007/s00138-024-01610-7</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Artificial intelligence ; Automation ; Calibration ; Communications Engineering ; Computer Science ; Computer vision ; Coordinates ; Eye (anatomy) ; Grasping (robotics) ; Image Processing and Computer Vision ; Image segmentation ; Industrial development ; Localization ; Localization method ; Motor rotors ; Networks ; Pattern Recognition ; Robots ; Workpieces</subject><ispartof>Machine vision and applications, 2024-11, Vol.35 (6), p.132, Article 132</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c200t-56a50042101a13736ea1dc03e4efe0f5b67cdcd0878350e64de9ac6fa00508983</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00138-024-01610-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00138-024-01610-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Liang, Jixin</creatorcontrib><creatorcontrib>Ye, Yuping</creatorcontrib><creatorcontrib>Wu, Di</creatorcontrib><creatorcontrib>Chen, Siyuan</creatorcontrib><creatorcontrib>Song, Zhan</creatorcontrib><title>High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor</title><title>Machine vision and applications</title><addtitle>Machine Vision and Applications</addtitle><description>With the rapid development of artificial intelligence and computer vision, numerous technologies have been introduced to automate manufacturing in the industry. Typical metal workpieces in the industry often have highly reflective surfaces, come in various sizes, and are positioned irregularly. The motor rotor presented in this paper is one such representative workpiece. Traditional grasping methods for workpiece loading and unloading are pre-programmed and often struggle to cope with complex and disordered situations. In this paper, we introduce a structured light (SL) sensor as the visual guide for the triaxial robot. Furthermore, we propose a high-precision hand-eye calibration method for the non-orthogonal coordinate system of the triaxial robot. Additionally, a motor rotor center localization method based on U-Net image segmentation is proposed. By combining the high-precision hand-eye calibration and localization, we can accurately and automatically locate and grasp the rotor. We have conducted sufficient experiments to verify the effectiveness and accuracy of our system.</description><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Calibration</subject><subject>Communications Engineering</subject><subject>Computer Science</subject><subject>Computer vision</subject><subject>Coordinates</subject><subject>Eye (anatomy)</subject><subject>Grasping (robotics)</subject><subject>Image Processing and Computer Vision</subject><subject>Image segmentation</subject><subject>Industrial development</subject><subject>Localization</subject><subject>Localization method</subject><subject>Motor rotors</subject><subject>Networks</subject><subject>Pattern Recognition</subject><subject>Robots</subject><subject>Workpieces</subject><issn>0932-8092</issn><issn>1432-1769</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LAzEQxYMoWKtfwFPAc3Sy2U12j1L_VCh40XNIs8m6pbupmSzYb29qBW9eZgbmvd8Mj5BrDrccQN0hABc1g6JkwCUHpk7IjJeiYFzJ5pTMoMlzDU1xTi4QNwBQKlXOyGbZdx_Med_b3o12T82UwmCSa2mKvfnqzZbGsA6JdtHgrh87intMbqA-RDqElGs8VKQTHrbigWKKk01TzIxtpieKbsQQL8mZN1t0V799Tt6fHt8WS7Z6fX5Z3K-YLQASq6Sp8ncFB264UEI6w1sLwpXOO_DVWirb2hZqVYsKnCxb1xgrvQGooG5qMSc3R-4uhs_JYdKbMMUxn9SC80KWEiqRVcVRZWNAjM7rXewHE_eagz5kqo-Z6pyp_slUq2wSRxNm8di5-If-x_UN-OR6_g</recordid><startdate>20241101</startdate><enddate>20241101</enddate><creator>Liang, Jixin</creator><creator>Ye, Yuping</creator><creator>Wu, Di</creator><creator>Chen, Siyuan</creator><creator>Song, Zhan</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20241101</creationdate><title>High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor</title><author>Liang, Jixin ; Ye, Yuping ; Wu, Di ; Chen, Siyuan ; Song, Zhan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c200t-56a50042101a13736ea1dc03e4efe0f5b67cdcd0878350e64de9ac6fa00508983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Artificial intelligence</topic><topic>Automation</topic><topic>Calibration</topic><topic>Communications Engineering</topic><topic>Computer Science</topic><topic>Computer vision</topic><topic>Coordinates</topic><topic>Eye (anatomy)</topic><topic>Grasping (robotics)</topic><topic>Image Processing and Computer Vision</topic><topic>Image segmentation</topic><topic>Industrial development</topic><topic>Localization</topic><topic>Localization method</topic><topic>Motor rotors</topic><topic>Networks</topic><topic>Pattern Recognition</topic><topic>Robots</topic><topic>Workpieces</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liang, Jixin</creatorcontrib><creatorcontrib>Ye, Yuping</creatorcontrib><creatorcontrib>Wu, Di</creatorcontrib><creatorcontrib>Chen, Siyuan</creatorcontrib><creatorcontrib>Song, Zhan</creatorcontrib><collection>CrossRef</collection><jtitle>Machine vision and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liang, Jixin</au><au>Ye, Yuping</au><au>Wu, Di</au><au>Chen, Siyuan</au><au>Song, Zhan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor</atitle><jtitle>Machine vision and applications</jtitle><stitle>Machine Vision and Applications</stitle><date>2024-11-01</date><risdate>2024</risdate><volume>35</volume><issue>6</issue><spage>132</spage><pages>132-</pages><artnum>132</artnum><issn>0932-8092</issn><eissn>1432-1769</eissn><abstract>With the rapid development of artificial intelligence and computer vision, numerous technologies have been introduced to automate manufacturing in the industry. Typical metal workpieces in the industry often have highly reflective surfaces, come in various sizes, and are positioned irregularly. The motor rotor presented in this paper is one such representative workpiece. Traditional grasping methods for workpiece loading and unloading are pre-programmed and often struggle to cope with complex and disordered situations. In this paper, we introduce a structured light (SL) sensor as the visual guide for the triaxial robot. Furthermore, we propose a high-precision hand-eye calibration method for the non-orthogonal coordinate system of the triaxial robot. Additionally, a motor rotor center localization method based on U-Net image segmentation is proposed. By combining the high-precision hand-eye calibration and localization, we can accurately and automatically locate and grasp the rotor. We have conducted sufficient experiments to verify the effectiveness and accuracy of our system.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00138-024-01610-7</doi></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0932-8092 |
| ispartof | Machine vision and applications, 2024-11, Vol.35 (6), p.132, Article 132 |
| issn | 0932-8092 1432-1769 |
| language | eng |
| recordid | cdi_proquest_journals_3112646053 |
| source | Springer Nature - Complete Springer Journals |
| subjects | Artificial intelligence Automation Calibration Communications Engineering Computer Science Computer vision Coordinates Eye (anatomy) Grasping (robotics) Image Processing and Computer Vision Image segmentation Industrial development Localization Localization method Motor rotors Networks Pattern Recognition Robots Workpieces |
| title | High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T22%3A06%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=High-efficiency%20automated%20triaxial%20robot%20grasping%20system%20for%20motor%20rotors%20using%203D%20structured%20light%20sensor&rft.jtitle=Machine%20vision%20and%20applications&rft.au=Liang,%20Jixin&rft.date=2024-11-01&rft.volume=35&rft.issue=6&rft.spage=132&rft.pages=132-&rft.artnum=132&rft.issn=0932-8092&rft.eissn=1432-1769&rft_id=info:doi/10.1007/s00138-024-01610-7&rft_dat=%3Cproquest_cross%3E3112646053%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3112646053&rft_id=info:pmid/&rfr_iscdi=true |