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A Novel Seam Tracking Technique with a Four-Step Method and Experimental Investigation of Robotic Welding Oriented to Complex Welding Seam
The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge de...
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Published in: | Sensors (Basel, Switzerland) Switzerland), 2021-04, Vol.21 (9), p.3067 |
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description | The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge detection, followed by joint width measurement, and, lastly, welding path position determination with respect to welding robot co-ordinate frame. A novel seam tracking technique with a four-step method is introduced. A laser sensor is used to scan grooves to obtain profile data, and the data are processed by a filtering algorithm to smooth the noise. The second derivative algorithm is proposed to initially position the feature points, and then linear fitting is performed to achieve precise positioning. The groove data are transformed into the robot's welding path through sensor pose calibration, which could realize real-time seam tracking. Experimental demonstration was carried out to verify the tracking effect of both straight and curved welding seams. Results show that the average deviations in the
direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both
and
direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research. |
doi_str_mv | 10.3390/s21093067 |
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direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both
and
direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research.</description><identifier>ISSN: 1424-8220</identifier><identifier>EISSN: 1424-8220</identifier><identifier>DOI: 10.3390/s21093067</identifier><identifier>PMID: 33924925</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Accuracy ; Algorithms ; Cameras ; complex welding seam ; Deviation ; Edge detection ; feature point extracting ; Grooves ; Industrial robots ; Laser beam welding ; laser sensor ; Lasers ; Position measurement ; Robot dynamics ; Robotics ; Robots ; seam tracking ; Sensors ; welding robot</subject><ispartof>Sensors (Basel, Switzerland), 2021-04, Vol.21 (9), p.3067</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c469t-e11b6df4381bd3157326cf309357f627da70b4688fb806519a8ef5753b9baad83</citedby><cites>FETCH-LOGICAL-c469t-e11b6df4381bd3157326cf309357f627da70b4688fb806519a8ef5753b9baad83</cites><orcidid>0000-0002-6725-182X ; 0000-0002-4736-1554 ; 0000-0002-3651-3639</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2530160964/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2530160964?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,882,25734,27905,27906,36993,36994,44571,53772,53774,74875</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33924925$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Gong</creatorcontrib><creatorcontrib>Zhang, Yuhang</creatorcontrib><creatorcontrib>Tuo, Shuaihua</creatorcontrib><creatorcontrib>Hou, Zhicheng</creatorcontrib><creatorcontrib>Yang, Wenlin</creatorcontrib><creatorcontrib>Xu, Zheng</creatorcontrib><creatorcontrib>Wu, Yueyu</creatorcontrib><creatorcontrib>Yuan, Hai</creatorcontrib><creatorcontrib>Shin, Kyoosik</creatorcontrib><title>A Novel Seam Tracking Technique with a Four-Step Method and Experimental Investigation of Robotic Welding Oriented to Complex Welding Seam</title><title>Sensors (Basel, Switzerland)</title><addtitle>Sensors (Basel)</addtitle><description>The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge detection, followed by joint width measurement, and, lastly, welding path position determination with respect to welding robot co-ordinate frame. A novel seam tracking technique with a four-step method is introduced. A laser sensor is used to scan grooves to obtain profile data, and the data are processed by a filtering algorithm to smooth the noise. The second derivative algorithm is proposed to initially position the feature points, and then linear fitting is performed to achieve precise positioning. The groove data are transformed into the robot's welding path through sensor pose calibration, which could realize real-time seam tracking. Experimental demonstration was carried out to verify the tracking effect of both straight and curved welding seams. Results show that the average deviations in the
direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both
and
direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Cameras</subject><subject>complex welding seam</subject><subject>Deviation</subject><subject>Edge detection</subject><subject>feature point extracting</subject><subject>Grooves</subject><subject>Industrial robots</subject><subject>Laser beam welding</subject><subject>laser sensor</subject><subject>Lasers</subject><subject>Position measurement</subject><subject>Robot dynamics</subject><subject>Robotics</subject><subject>Robots</subject><subject>seam tracking</subject><subject>Sensors</subject><subject>welding robot</subject><issn>1424-8220</issn><issn>1424-8220</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdks1u1DAQgCMEoqVw4AWQJS5wCPgn_rsgVau2rFSoRBdxtJx4susliVPHu7SvwFPjZcuq5WTL8_nzzHiK4jXBHxjT-ONECdYMC_mkOCYVrUpFKX76YH9UvJimNcaUMaaeF0f5Fq005cfF71P0NWyhQ9dge7SItvnphyVaQLMa_M0G0C-fVsii87CJ5XWCEX2BtAoO2cGhs9sRou9hSLZD82ELU_JLm3wYUGjRt1CH5Bv0Azq3c15Fn0lwKAU0C_3Ywe0htnv9ZfGstd0Er-7Xk-L7-dli9rm8vLqYz04vy6YSOpVASC1cWzFFascIl4yKpmW5AVy2gkpnJa4roVRbKyw40VZByyVnta6tdYqdFPO91wW7NmMuwMY7E6w3fw9CXBobc-IdmKyVrBGYA1FVS7TOdg4giQMqK22z69PeNW7qHlyTC4y2eyR9HBn8yizD1ihCeYVJFry7F8SQ2z0l0_upga6zA4TNZCinWHEm9Q59-x-6zp8y5FZlimEisBZVpt7vqSaGaYrQHpIh2OymxRymJbNvHmZ_IP-NB_sDpty6JQ</recordid><startdate>20210428</startdate><enddate>20210428</enddate><creator>Zhang, Gong</creator><creator>Zhang, Yuhang</creator><creator>Tuo, Shuaihua</creator><creator>Hou, Zhicheng</creator><creator>Yang, Wenlin</creator><creator>Xu, Zheng</creator><creator>Wu, Yueyu</creator><creator>Yuan, Hai</creator><creator>Shin, Kyoosik</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-6725-182X</orcidid><orcidid>https://orcid.org/0000-0002-4736-1554</orcidid><orcidid>https://orcid.org/0000-0002-3651-3639</orcidid></search><sort><creationdate>20210428</creationdate><title>A Novel Seam Tracking Technique with a Four-Step Method and Experimental Investigation of Robotic Welding Oriented to Complex Welding Seam</title><author>Zhang, Gong ; Zhang, Yuhang ; Tuo, Shuaihua ; Hou, Zhicheng ; Yang, Wenlin ; Xu, Zheng ; Wu, Yueyu ; Yuan, Hai ; Shin, Kyoosik</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c469t-e11b6df4381bd3157326cf309357f627da70b4688fb806519a8ef5753b9baad83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Cameras</topic><topic>complex welding seam</topic><topic>Deviation</topic><topic>Edge detection</topic><topic>feature point extracting</topic><topic>Grooves</topic><topic>Industrial robots</topic><topic>Laser beam welding</topic><topic>laser sensor</topic><topic>Lasers</topic><topic>Position measurement</topic><topic>Robot dynamics</topic><topic>Robotics</topic><topic>Robots</topic><topic>seam tracking</topic><topic>Sensors</topic><topic>welding robot</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Gong</creatorcontrib><creatorcontrib>Zhang, Yuhang</creatorcontrib><creatorcontrib>Tuo, Shuaihua</creatorcontrib><creatorcontrib>Hou, Zhicheng</creatorcontrib><creatorcontrib>Yang, Wenlin</creatorcontrib><creatorcontrib>Xu, Zheng</creatorcontrib><creatorcontrib>Wu, Yueyu</creatorcontrib><creatorcontrib>Yuan, Hai</creatorcontrib><creatorcontrib>Shin, Kyoosik</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content (ProQuest)</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><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Sensors (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Gong</au><au>Zhang, Yuhang</au><au>Tuo, Shuaihua</au><au>Hou, Zhicheng</au><au>Yang, Wenlin</au><au>Xu, Zheng</au><au>Wu, Yueyu</au><au>Yuan, Hai</au><au>Shin, Kyoosik</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Novel Seam Tracking Technique with a Four-Step Method and Experimental Investigation of Robotic Welding Oriented to Complex Welding Seam</atitle><jtitle>Sensors (Basel, Switzerland)</jtitle><addtitle>Sensors (Basel)</addtitle><date>2021-04-28</date><risdate>2021</risdate><volume>21</volume><issue>9</issue><spage>3067</spage><pages>3067-</pages><issn>1424-8220</issn><eissn>1424-8220</eissn><abstract>The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge detection, followed by joint width measurement, and, lastly, welding path position determination with respect to welding robot co-ordinate frame. A novel seam tracking technique with a four-step method is introduced. A laser sensor is used to scan grooves to obtain profile data, and the data are processed by a filtering algorithm to smooth the noise. The second derivative algorithm is proposed to initially position the feature points, and then linear fitting is performed to achieve precise positioning. The groove data are transformed into the robot's welding path through sensor pose calibration, which could realize real-time seam tracking. Experimental demonstration was carried out to verify the tracking effect of both straight and curved welding seams. Results show that the average deviations in the
direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both
and
direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>33924925</pmid><doi>10.3390/s21093067</doi><orcidid>https://orcid.org/0000-0002-6725-182X</orcidid><orcidid>https://orcid.org/0000-0002-4736-1554</orcidid><orcidid>https://orcid.org/0000-0002-3651-3639</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Algorithms Cameras complex welding seam Deviation Edge detection feature point extracting Grooves Industrial robots Laser beam welding laser sensor Lasers Position measurement Robot dynamics Robotics Robots seam tracking Sensors welding robot |
title | A Novel Seam Tracking Technique with a Four-Step Method and Experimental Investigation of Robotic Welding Oriented to Complex Welding Seam |
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