Precise pose and assembly detection of generic tubular joints based on partial scan data
Intelligent and accurate determination of the position and orientation, or pose, of a workpiece which is manually placed is essential for automating fabrication tasks such as welding. In this paper, a novel algorithm based on minimizing the area of a boundary enclosing partial scan data points is pr...
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Veröffentlicht in: | Neural computing & applications 2022-04, Vol.34 (7), p.5201-5211 |
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creator | Tan, Yan Zhi Pang, Chee Khiang Al Mamun, Abdullah Wong, Fook Seng Chew, Chee Meng |
description | Intelligent and accurate determination of the position and orientation, or pose, of a workpiece which is manually placed is essential for automating fabrication tasks such as welding. In this paper, a novel algorithm based on minimizing the area of a boundary enclosing partial scan data points is proposed for detecting both the pose and assembly of tubular joints with the aid of reference ideal models. The proposed algorithm can also be applied to tubular joints with non-cylindrical cross sections. The fit-up information obtained can be used to determine whether realignment is required or combined with the pose information to re-plan paths for subsequent tasks. The focus of existing state-of-the-art is on objects with features, and the localization of featureless objects such as generic tubular joints using partial and sparse scan data remains a challenge. The proposed algorithm is applied to an actual robotic welding system to locate a tubular workpiece. Experiment results using the scan data as ground truth show that root mean square error is less than 1% of the pipe diameters, considering both brace and chord components with diameters greater than 200 mm. |
doi_str_mv | 10.1007/s00521-021-06246-6 |
format | Article |
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In this paper, a novel algorithm based on minimizing the area of a boundary enclosing partial scan data points is proposed for detecting both the pose and assembly of tubular joints with the aid of reference ideal models. The proposed algorithm can also be applied to tubular joints with non-cylindrical cross sections. The fit-up information obtained can be used to determine whether realignment is required or combined with the pose information to re-plan paths for subsequent tasks. The focus of existing state-of-the-art is on objects with features, and the localization of featureless objects such as generic tubular joints using partial and sparse scan data remains a challenge. The proposed algorithm is applied to an actual robotic welding system to locate a tubular workpiece. Experiment results using the scan data as ground truth show that root mean square error is less than 1% of the pipe diameters, considering both brace and chord components with diameters greater than 200 mm.</description><identifier>ISSN: 0941-0643</identifier><identifier>EISSN: 1433-3058</identifier><identifier>DOI: 10.1007/s00521-021-06246-6</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>Algorithms ; Artificial Intelligence ; Assembly ; Computational Biology/Bioinformatics ; Computational Science and Engineering ; Computer Science ; Data Mining and Knowledge Discovery ; Data points ; Image Processing and Computer Vision ; Probability and Statistics in Computer Science ; Realignment ; Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems ; Welding ; Workpieces</subject><ispartof>Neural computing & applications, 2022-04, Vol.34 (7), p.5201-5211</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-b5c1366238f5ddef3b1d1abc5dc759e36ad1c3d62b2837d20450fe319ee63a593</citedby><cites>FETCH-LOGICAL-c319t-b5c1366238f5ddef3b1d1abc5dc759e36ad1c3d62b2837d20450fe319ee63a593</cites><orcidid>0000-0001-8260-5879</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00521-021-06246-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00521-021-06246-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Tan, Yan Zhi</creatorcontrib><creatorcontrib>Pang, Chee Khiang</creatorcontrib><creatorcontrib>Al Mamun, Abdullah</creatorcontrib><creatorcontrib>Wong, Fook Seng</creatorcontrib><creatorcontrib>Chew, Chee Meng</creatorcontrib><title>Precise pose and assembly detection of generic tubular joints based on partial scan data</title><title>Neural computing & applications</title><addtitle>Neural Comput & Applic</addtitle><description>Intelligent and accurate determination of the position and orientation, or pose, of a workpiece which is manually placed is essential for automating fabrication tasks such as welding. In this paper, a novel algorithm based on minimizing the area of a boundary enclosing partial scan data points is proposed for detecting both the pose and assembly of tubular joints with the aid of reference ideal models. The proposed algorithm can also be applied to tubular joints with non-cylindrical cross sections. The fit-up information obtained can be used to determine whether realignment is required or combined with the pose information to re-plan paths for subsequent tasks. The focus of existing state-of-the-art is on objects with features, and the localization of featureless objects such as generic tubular joints using partial and sparse scan data remains a challenge. The proposed algorithm is applied to an actual robotic welding system to locate a tubular workpiece. Experiment results using the scan data as ground truth show that root mean square error is less than 1% of the pipe diameters, considering both brace and chord components with diameters greater than 200 mm.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Assembly</subject><subject>Computational Biology/Bioinformatics</subject><subject>Computational Science and Engineering</subject><subject>Computer Science</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Data points</subject><subject>Image Processing and Computer Vision</subject><subject>Probability and Statistics in Computer Science</subject><subject>Realignment</subject><subject>Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems</subject><subject>Welding</subject><subject>Workpieces</subject><issn>0941-0643</issn><issn>1433-3058</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kE9LxDAQxYMouK5-AU8Bz9VJpsm2R1n8Bwt6UPAW0mS6dOm2NUkPfntbKnjzMDOHeb83zGPsWsCtANjcRQAlRQZzaZnrTJ-wlcgRMwRVnLIVlPm8yvGcXcR4AIBcF2rFPt8CuSYSH_qp2c5zGyMdq_abe0rkUtN3vK_5njoKjeNprMbWBn7omy5FXtlInk-SwYbU2JZHZzvubbKX7Ky2baSr37lmH48P79vnbPf69LK932UORZmySjmBWkssauU91VgJL2zllHcbVRJq64VDr2UlC9x4CbmCmiaUSKNVJa7ZzeI7hP5rpJjMoR9DN500UmMpJIrp6zWTi8qFPsZAtRlCc7Th2wgwc4JmSdDAXHOCRk8QLlCcxN2ewp_1P9QPViZz6g</recordid><startdate>20220401</startdate><enddate>20220401</enddate><creator>Tan, Yan Zhi</creator><creator>Pang, Chee Khiang</creator><creator>Al Mamun, Abdullah</creator><creator>Wong, Fook Seng</creator><creator>Chew, Chee Meng</creator><general>Springer London</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0001-8260-5879</orcidid></search><sort><creationdate>20220401</creationdate><title>Precise pose and assembly detection of generic tubular joints based on partial scan data</title><author>Tan, Yan Zhi ; Pang, Chee Khiang ; Al Mamun, Abdullah ; Wong, Fook Seng ; Chew, Chee Meng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-b5c1366238f5ddef3b1d1abc5dc759e36ad1c3d62b2837d20450fe319ee63a593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Assembly</topic><topic>Computational Biology/Bioinformatics</topic><topic>Computational Science and Engineering</topic><topic>Computer Science</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Data points</topic><topic>Image Processing and Computer Vision</topic><topic>Probability and Statistics in Computer Science</topic><topic>Realignment</topic><topic>Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems</topic><topic>Welding</topic><topic>Workpieces</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tan, Yan Zhi</creatorcontrib><creatorcontrib>Pang, Chee Khiang</creatorcontrib><creatorcontrib>Al Mamun, Abdullah</creatorcontrib><creatorcontrib>Wong, Fook Seng</creatorcontrib><creatorcontrib>Chew, Chee Meng</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Neural computing & applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tan, Yan Zhi</au><au>Pang, Chee Khiang</au><au>Al Mamun, Abdullah</au><au>Wong, Fook Seng</au><au>Chew, Chee Meng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Precise pose and assembly detection of generic tubular joints based on partial scan data</atitle><jtitle>Neural computing & applications</jtitle><stitle>Neural Comput & Applic</stitle><date>2022-04-01</date><risdate>2022</risdate><volume>34</volume><issue>7</issue><spage>5201</spage><epage>5211</epage><pages>5201-5211</pages><issn>0941-0643</issn><eissn>1433-3058</eissn><abstract>Intelligent and accurate determination of the position and orientation, or pose, of a workpiece which is manually placed is essential for automating fabrication tasks such as welding. In this paper, a novel algorithm based on minimizing the area of a boundary enclosing partial scan data points is proposed for detecting both the pose and assembly of tubular joints with the aid of reference ideal models. The proposed algorithm can also be applied to tubular joints with non-cylindrical cross sections. The fit-up information obtained can be used to determine whether realignment is required or combined with the pose information to re-plan paths for subsequent tasks. The focus of existing state-of-the-art is on objects with features, and the localization of featureless objects such as generic tubular joints using partial and sparse scan data remains a challenge. The proposed algorithm is applied to an actual robotic welding system to locate a tubular workpiece. 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subjects | Algorithms Artificial Intelligence Assembly Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Data points Image Processing and Computer Vision Probability and Statistics in Computer Science Realignment Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems Welding Workpieces |
title | Precise pose and assembly detection of generic tubular joints based on partial scan data |
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