Locating End-Effector Tips in Robotic Micromanipulation
In robotic micromanipulation, end-effector tips must be first located under microscopy imaging before manipulation is performed. The tip of micromanipulation tools is typically a few micrometers in size and highly delicate. In all existing micromanipulation systems, the process of locating the end-e...
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Veröffentlicht in: | IEEE transactions on robotics 2014-02, Vol.30 (1), p.125-130 |
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creator | Jun Liu Zheng Gong Tang, Kathryn Zhe Lu Changhai Ru Jun Luo Shaorong Xie Yu Sun |
description | In robotic micromanipulation, end-effector tips must be first located under microscopy imaging before manipulation is performed. The tip of micromanipulation tools is typically a few micrometers in size and highly delicate. In all existing micromanipulation systems, the process of locating the end-effector tip is conducted by a skilled operator, and the automation of this task has not been attempted. This paper presents a technique to automatically locate end-effector tips. The technique consists of programmed sweeping patterns, motion history image end-effector detection, active contour to estimate end-effector positions, autofocusing and quad-tree search to locate an end-effector tip, and, finally, visual servoing to position the tip to the center of the field of view. Two types of micromanipulation tools (micropipette that represents single-ended tools and microgripper that represents multiended tools) were used in experiments for testing. Quantitative results are reported in the speed and success rate of the autolocating technique, based on over 500 trials. Furthermore, the effect of factors such as imaging mode and image processing parameter selections was also quantitatively discussed. Guidelines are provided for the implementation of the technique in order to achieve high efficiency and success rates. |
doi_str_mv | 10.1109/TRO.2013.2280060 |
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The tip of micromanipulation tools is typically a few micrometers in size and highly delicate. In all existing micromanipulation systems, the process of locating the end-effector tip is conducted by a skilled operator, and the automation of this task has not been attempted. This paper presents a technique to automatically locate end-effector tips. The technique consists of programmed sweeping patterns, motion history image end-effector detection, active contour to estimate end-effector positions, autofocusing and quad-tree search to locate an end-effector tip, and, finally, visual servoing to position the tip to the center of the field of view. Two types of micromanipulation tools (micropipette that represents single-ended tools and microgripper that represents multiended tools) were used in experiments for testing. Quantitative results are reported in the speed and success rate of the autolocating technique, based on over 500 trials. Furthermore, the effect of factors such as imaging mode and image processing parameter selections was also quantitatively discussed. Guidelines are provided for the implementation of the technique in order to achieve high efficiency and success rates.</description><identifier>ISSN: 1552-3098</identifier><identifier>EISSN: 1941-0468</identifier><identifier>DOI: 10.1109/TRO.2013.2280060</identifier><identifier>CODEN: ITREAE</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Active contours ; Autofocusing ; Automation ; Efficiency ; end-effector detection ; Grippers ; Image detection ; Imaging ; Kalman filters ; locating end-effector tips ; Micromanipulation ; Micrometers ; Microscopy ; Radio frequency ; robotic micromanipulation ; Robotics ; Searching ; Tips</subject><ispartof>IEEE transactions on robotics, 2014-02, Vol.30 (1), p.125-130</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Feb 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c366t-812a7cb6146dcbe670184dc99396da873a22750d6b6f597fec042f55e50530693</citedby><cites>FETCH-LOGICAL-c366t-812a7cb6146dcbe670184dc99396da873a22750d6b6f597fec042f55e50530693</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6589998$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27923,27924,54757</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6589998$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jun Liu</creatorcontrib><creatorcontrib>Zheng Gong</creatorcontrib><creatorcontrib>Tang, Kathryn</creatorcontrib><creatorcontrib>Zhe Lu</creatorcontrib><creatorcontrib>Changhai Ru</creatorcontrib><creatorcontrib>Jun Luo</creatorcontrib><creatorcontrib>Shaorong Xie</creatorcontrib><creatorcontrib>Yu Sun</creatorcontrib><title>Locating End-Effector Tips in Robotic Micromanipulation</title><title>IEEE transactions on robotics</title><addtitle>TRO</addtitle><description>In robotic micromanipulation, end-effector tips must be first located under microscopy imaging before manipulation is performed. The tip of micromanipulation tools is typically a few micrometers in size and highly delicate. In all existing micromanipulation systems, the process of locating the end-effector tip is conducted by a skilled operator, and the automation of this task has not been attempted. This paper presents a technique to automatically locate end-effector tips. The technique consists of programmed sweeping patterns, motion history image end-effector detection, active contour to estimate end-effector positions, autofocusing and quad-tree search to locate an end-effector tip, and, finally, visual servoing to position the tip to the center of the field of view. Two types of micromanipulation tools (micropipette that represents single-ended tools and microgripper that represents multiended tools) were used in experiments for testing. Quantitative results are reported in the speed and success rate of the autolocating technique, based on over 500 trials. Furthermore, the effect of factors such as imaging mode and image processing parameter selections was also quantitatively discussed. Guidelines are provided for the implementation of the technique in order to achieve high efficiency and success rates.</description><subject>Active contours</subject><subject>Autofocusing</subject><subject>Automation</subject><subject>Efficiency</subject><subject>end-effector detection</subject><subject>Grippers</subject><subject>Image detection</subject><subject>Imaging</subject><subject>Kalman filters</subject><subject>locating end-effector tips</subject><subject>Micromanipulation</subject><subject>Micrometers</subject><subject>Microscopy</subject><subject>Radio frequency</subject><subject>robotic micromanipulation</subject><subject>Robotics</subject><subject>Searching</subject><subject>Tips</subject><issn>1552-3098</issn><issn>1941-0468</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkDtrwzAURkVpoeljL3QxdOni9OotjSWkD0gJhHQWsiwXBcdyLXvov69CQodO9w7nu4-D0B2GOcagn7ab9ZwApnNCFICAMzTDmuESmFDnueeclBS0ukRXKe0ACNNAZ0iuorNj6L6KZVeXy6bxboxDsQ19KkJXbGIVx-CKj-CGuLdd6Kc247G7QReNbZO_PdVr9Pmy3C7eytX69X3xvCodFWIsFSZWukpgJmpXeSEBK1Y7rakWtVWSWkIkh1pUouFa5u3ASMO558ApCE2v0eNxbj_E78mn0exDcr5tbefjlAzmBLSkjMqMPvxDd3EaunydwUxLoEKKAwVHKj-U0uAb0w9hb4cfg8EcTJps0hxMmpPJHLk_RoL3_g8XXGmtFf0FpIdspQ</recordid><startdate>20140201</startdate><enddate>20140201</enddate><creator>Jun Liu</creator><creator>Zheng Gong</creator><creator>Tang, Kathryn</creator><creator>Zhe Lu</creator><creator>Changhai Ru</creator><creator>Jun Luo</creator><creator>Shaorong Xie</creator><creator>Yu Sun</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><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></search><sort><creationdate>20140201</creationdate><title>Locating End-Effector Tips in Robotic Micromanipulation</title><author>Jun Liu ; Zheng Gong ; Tang, Kathryn ; Zhe Lu ; Changhai Ru ; Jun Luo ; Shaorong Xie ; Yu Sun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c366t-812a7cb6146dcbe670184dc99396da873a22750d6b6f597fec042f55e50530693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Active contours</topic><topic>Autofocusing</topic><topic>Automation</topic><topic>Efficiency</topic><topic>end-effector detection</topic><topic>Grippers</topic><topic>Image detection</topic><topic>Imaging</topic><topic>Kalman filters</topic><topic>locating end-effector tips</topic><topic>Micromanipulation</topic><topic>Micrometers</topic><topic>Microscopy</topic><topic>Radio frequency</topic><topic>robotic micromanipulation</topic><topic>Robotics</topic><topic>Searching</topic><topic>Tips</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jun Liu</creatorcontrib><creatorcontrib>Zheng Gong</creatorcontrib><creatorcontrib>Tang, Kathryn</creatorcontrib><creatorcontrib>Zhe Lu</creatorcontrib><creatorcontrib>Changhai Ru</creatorcontrib><creatorcontrib>Jun Luo</creatorcontrib><creatorcontrib>Shaorong Xie</creatorcontrib><creatorcontrib>Yu Sun</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><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><jtitle>IEEE transactions on robotics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jun Liu</au><au>Zheng Gong</au><au>Tang, Kathryn</au><au>Zhe Lu</au><au>Changhai Ru</au><au>Jun Luo</au><au>Shaorong Xie</au><au>Yu Sun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Locating End-Effector Tips in Robotic Micromanipulation</atitle><jtitle>IEEE transactions on robotics</jtitle><stitle>TRO</stitle><date>2014-02-01</date><risdate>2014</risdate><volume>30</volume><issue>1</issue><spage>125</spage><epage>130</epage><pages>125-130</pages><issn>1552-3098</issn><eissn>1941-0468</eissn><coden>ITREAE</coden><abstract>In robotic micromanipulation, end-effector tips must be first located under microscopy imaging before manipulation is performed. The tip of micromanipulation tools is typically a few micrometers in size and highly delicate. In all existing micromanipulation systems, the process of locating the end-effector tip is conducted by a skilled operator, and the automation of this task has not been attempted. This paper presents a technique to automatically locate end-effector tips. The technique consists of programmed sweeping patterns, motion history image end-effector detection, active contour to estimate end-effector positions, autofocusing and quad-tree search to locate an end-effector tip, and, finally, visual servoing to position the tip to the center of the field of view. Two types of micromanipulation tools (micropipette that represents single-ended tools and microgripper that represents multiended tools) were used in experiments for testing. Quantitative results are reported in the speed and success rate of the autolocating technique, based on over 500 trials. 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subjects | Active contours Autofocusing Automation Efficiency end-effector detection Grippers Image detection Imaging Kalman filters locating end-effector tips Micromanipulation Micrometers Microscopy Radio frequency robotic micromanipulation Robotics Searching Tips |
title | Locating End-Effector Tips in Robotic Micromanipulation |
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