Choosing Measurement Poses for Robot Calibration with the Local Convergence Method and Tabu Search
The robustness of robot calibration with respect to sensor noise is sensitive to the manipulator poses used to collect measurement data. In this paper we propose an algorithm based on a constrained optimization method, which allows us to choose a set of measurement configurations. It works by select...
Gespeichert in:
| Veröffentlicht in: | The International journal of robotics research 2005-06, Vol.24 (6), p.501-518 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 518 |
|---|---|
| container_issue | 6 |
| container_start_page | 501 |
| container_title | The International journal of robotics research |
| container_volume | 24 |
| creator | Daney, David Papegay, Yves Madeline, Blaise |
| description | The robustness of robot calibration with respect to sensor noise is sensitive to the manipulator poses used to collect measurement data. In this paper we propose an algorithm based on a constrained optimization method, which allows us to choose a set of measurement configurations. It works by selecting iteratively one pose after another inside the workspace. After a few steps, a set of configurations is obtained, which maximizes an index of observability associated with the identification Jacobian. This algorithm has been shown, in a former work, to be sensitive to local minima. This is why we propose here meta-heuristic methods to decrease this sensibility of our algorithm. Finally, a validation through the simulation of a calibration experience shows that using selected configurations significantly improve the kinematic parameter identification by dividing by 10-15 the noise associated with the results. Also, we present an application to the calibration of a parallel robot with a vision-based measurement device. |
| doi_str_mv | 10.1177/0278364905053185 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_00907749v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A140995846</galeid><sage_id>10.1177_0278364905053185</sage_id><sourcerecordid>A140995846</sourcerecordid><originalsourceid>FETCH-LOGICAL-c443t-caa5f99e48d4fca034aadcc23e4581798b2a2df90c4ded4485c95b3c45dbb2b3</originalsourceid><addsrcrecordid>eNqFkc-L1TAQx4so-Fy9ewweBA9dJ03y0hwfRV3hiaLvHqbp9DVLX7Im7Yr_vS0VhQWROQzM9_OdH0xRvORwzbnWb6HStdhLAwqU4LV6VOy4lrwUXO8fF7tVLlf9afEs51sAEHswu6JthhizD2f2iTDPiS4UJvYlZsqsj4l9jW2cWIOjbxNOPgb2w08DmwZix-hwZE0M95TOFBwtLaYhdgxDx07YzuwbYXLD8-JJj2OmF7_zVXF6_-7U3JTHzx8-Nodj6aQUU-kQVW8MybqTvUMQErFzrhIkVc21qdsKq6434GRHnZS1cka1wknVtW3ViqvizdZ2wNHeJX_B9NNG9PbmcLRrDcCA1tLc84V9vbF3KX6fKU_24rOjccRAcc62MrwyQpv_g7XUUvMVfPUAvI1zCsu9thIAFRi1jr3eoDOOZH3o45TQLdHRxbsYqPdL_cAlGKNquV8MsBlcijkn6v8cxsGub7cP375Yys2S8Ux_l_gn_wtl0atH</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>230020951</pqid></control><display><type>article</type><title>Choosing Measurement Poses for Robot Calibration with the Local Convergence Method and Tabu Search</title><source>SAGE Complete A-Z List</source><creator>Daney, David ; Papegay, Yves ; Madeline, Blaise</creator><creatorcontrib>Daney, David ; Papegay, Yves ; Madeline, Blaise</creatorcontrib><description>The robustness of robot calibration with respect to sensor noise is sensitive to the manipulator poses used to collect measurement data. In this paper we propose an algorithm based on a constrained optimization method, which allows us to choose a set of measurement configurations. It works by selecting iteratively one pose after another inside the workspace. After a few steps, a set of configurations is obtained, which maximizes an index of observability associated with the identification Jacobian. This algorithm has been shown, in a former work, to be sensitive to local minima. This is why we propose here meta-heuristic methods to decrease this sensibility of our algorithm. Finally, a validation through the simulation of a calibration experience shows that using selected configurations significantly improve the kinematic parameter identification by dividing by 10-15 the noise associated with the results. Also, we present an application to the calibration of a parallel robot with a vision-based measurement device.</description><identifier>ISSN: 0278-3649</identifier><identifier>EISSN: 1741-3176</identifier><identifier>DOI: 10.1177/0278364905053185</identifier><identifier>CODEN: IJRREL</identifier><language>eng</language><publisher>London: SAGE Publications</publisher><subject>Calibration ; Computer Science ; Measurement techniques ; Optimization algorithms ; Parameter identification ; Robotics ; Robots ; Robust statistics ; Sensors</subject><ispartof>The International journal of robotics research, 2005-06, Vol.24 (6), p.501-518</ispartof><rights>COPYRIGHT 2005 Sage Publications Ltd. (UK)</rights><rights>Copyright SAGE PUBLICATIONS, INC. Jun 2005</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c443t-caa5f99e48d4fca034aadcc23e4581798b2a2df90c4ded4485c95b3c45dbb2b3</citedby><cites>FETCH-LOGICAL-c443t-caa5f99e48d4fca034aadcc23e4581798b2a2df90c4ded4485c95b3c45dbb2b3</cites><orcidid>0000-0001-8538-5875 ; 0000-0002-0847-7423</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0278364905053185$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0278364905053185$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>230,314,780,784,885,21818,27923,27924,43620,43621</link.rule.ids><backlink>$$Uhttps://inria.hal.science/hal-00907749$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Daney, David</creatorcontrib><creatorcontrib>Papegay, Yves</creatorcontrib><creatorcontrib>Madeline, Blaise</creatorcontrib><title>Choosing Measurement Poses for Robot Calibration with the Local Convergence Method and Tabu Search</title><title>The International journal of robotics research</title><description>The robustness of robot calibration with respect to sensor noise is sensitive to the manipulator poses used to collect measurement data. In this paper we propose an algorithm based on a constrained optimization method, which allows us to choose a set of measurement configurations. It works by selecting iteratively one pose after another inside the workspace. After a few steps, a set of configurations is obtained, which maximizes an index of observability associated with the identification Jacobian. This algorithm has been shown, in a former work, to be sensitive to local minima. This is why we propose here meta-heuristic methods to decrease this sensibility of our algorithm. Finally, a validation through the simulation of a calibration experience shows that using selected configurations significantly improve the kinematic parameter identification by dividing by 10-15 the noise associated with the results. Also, we present an application to the calibration of a parallel robot with a vision-based measurement device.</description><subject>Calibration</subject><subject>Computer Science</subject><subject>Measurement techniques</subject><subject>Optimization algorithms</subject><subject>Parameter identification</subject><subject>Robotics</subject><subject>Robots</subject><subject>Robust statistics</subject><subject>Sensors</subject><issn>0278-3649</issn><issn>1741-3176</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNqFkc-L1TAQx4so-Fy9ewweBA9dJ03y0hwfRV3hiaLvHqbp9DVLX7Im7Yr_vS0VhQWROQzM9_OdH0xRvORwzbnWb6HStdhLAwqU4LV6VOy4lrwUXO8fF7tVLlf9afEs51sAEHswu6JthhizD2f2iTDPiS4UJvYlZsqsj4l9jW2cWIOjbxNOPgb2w08DmwZix-hwZE0M95TOFBwtLaYhdgxDx07YzuwbYXLD8-JJj2OmF7_zVXF6_-7U3JTHzx8-Nodj6aQUU-kQVW8MybqTvUMQErFzrhIkVc21qdsKq6434GRHnZS1cka1wknVtW3ViqvizdZ2wNHeJX_B9NNG9PbmcLRrDcCA1tLc84V9vbF3KX6fKU_24rOjccRAcc62MrwyQpv_g7XUUvMVfPUAvI1zCsu9thIAFRi1jr3eoDOOZH3o45TQLdHRxbsYqPdL_cAlGKNquV8MsBlcijkn6v8cxsGub7cP375Yys2S8Ux_l_gn_wtl0atH</recordid><startdate>20050601</startdate><enddate>20050601</enddate><creator>Daney, David</creator><creator>Papegay, Yves</creator><creator>Madeline, Blaise</creator><general>SAGE Publications</general><general>Sage Publications Ltd. (UK)</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0001-8538-5875</orcidid><orcidid>https://orcid.org/0000-0002-0847-7423</orcidid></search><sort><creationdate>20050601</creationdate><title>Choosing Measurement Poses for Robot Calibration with the Local Convergence Method and Tabu Search</title><author>Daney, David ; Papegay, Yves ; Madeline, Blaise</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c443t-caa5f99e48d4fca034aadcc23e4581798b2a2df90c4ded4485c95b3c45dbb2b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Calibration</topic><topic>Computer Science</topic><topic>Measurement techniques</topic><topic>Optimization algorithms</topic><topic>Parameter identification</topic><topic>Robotics</topic><topic>Robots</topic><topic>Robust statistics</topic><topic>Sensors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Daney, David</creatorcontrib><creatorcontrib>Papegay, Yves</creatorcontrib><creatorcontrib>Madeline, Blaise</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>The International journal of robotics research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Daney, David</au><au>Papegay, Yves</au><au>Madeline, Blaise</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Choosing Measurement Poses for Robot Calibration with the Local Convergence Method and Tabu Search</atitle><jtitle>The International journal of robotics research</jtitle><date>2005-06-01</date><risdate>2005</risdate><volume>24</volume><issue>6</issue><spage>501</spage><epage>518</epage><pages>501-518</pages><issn>0278-3649</issn><eissn>1741-3176</eissn><coden>IJRREL</coden><abstract>The robustness of robot calibration with respect to sensor noise is sensitive to the manipulator poses used to collect measurement data. In this paper we propose an algorithm based on a constrained optimization method, which allows us to choose a set of measurement configurations. It works by selecting iteratively one pose after another inside the workspace. After a few steps, a set of configurations is obtained, which maximizes an index of observability associated with the identification Jacobian. This algorithm has been shown, in a former work, to be sensitive to local minima. This is why we propose here meta-heuristic methods to decrease this sensibility of our algorithm. Finally, a validation through the simulation of a calibration experience shows that using selected configurations significantly improve the kinematic parameter identification by dividing by 10-15 the noise associated with the results. Also, we present an application to the calibration of a parallel robot with a vision-based measurement device.</abstract><cop>London</cop><pub>SAGE Publications</pub><doi>10.1177/0278364905053185</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0001-8538-5875</orcidid><orcidid>https://orcid.org/0000-0002-0847-7423</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0278-3649 |
| ispartof | The International journal of robotics research, 2005-06, Vol.24 (6), p.501-518 |
| issn | 0278-3649 1741-3176 |
| language | eng |
| recordid | cdi_hal_primary_oai_HAL_hal_00907749v1 |
| source | SAGE Complete A-Z List |
| subjects | Calibration Computer Science Measurement techniques Optimization algorithms Parameter identification Robotics Robots Robust statistics Sensors |
| title | Choosing Measurement Poses for Robot Calibration with the Local Convergence Method and Tabu Search |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T12%3A27%3A15IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Choosing%20Measurement%20Poses%20for%20Robot%20Calibration%20with%20the%20Local%20Convergence%20Method%20and%20Tabu%20Search&rft.jtitle=The%20International%20journal%20of%20robotics%20research&rft.au=Daney,%20David&rft.date=2005-06-01&rft.volume=24&rft.issue=6&rft.spage=501&rft.epage=518&rft.pages=501-518&rft.issn=0278-3649&rft.eissn=1741-3176&rft.coden=IJRREL&rft_id=info:doi/10.1177/0278364905053185&rft_dat=%3Cgale_hal_p%3EA140995846%3C/gale_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=230020951&rft_id=info:pmid/&rft_galeid=A140995846&rft_sage_id=10.1177_0278364905053185&rfr_iscdi=true |