Statistical visual-dynamic model for hand-eye coordination
This paper introduces a new statistical method for combining vision and robot dynamics to generate trajectories to intercept a moving object. Previous methods only use information from the kinematics without considering the forces needed to move along the trajectory. Using robot dynamics allows extr...
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| creator | Beale, D Iravani, P Hall, P |
| description | This paper introduces a new statistical method for combining vision and robot dynamics to generate trajectories to intercept a moving object. Previous methods only use information from the kinematics without considering the forces needed to move along the trajectory. Using robot dynamics allows extra measures, such as energy efficiency, to be optimised alongside maximising the likelihood of intercepting the target. We derive a statistical model for a vision system and a Lagrangian dynamical model of a robotic arm, showing how to relate joint torques to the vision. The method is tested by applying it to the problem of catching a simulated moving object. |
| doi_str_mv | 10.1109/IROS.2010.5648832 |
| format | Conference Proceeding |
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Previous methods only use information from the kinematics without considering the forces needed to move along the trajectory. Using robot dynamics allows extra measures, such as energy efficiency, to be optimised alongside maximising the likelihood of intercepting the target. We derive a statistical model for a vision system and a Lagrangian dynamical model of a robotic arm, showing how to relate joint torques to the vision. 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Previous methods only use information from the kinematics without considering the forces needed to move along the trajectory. Using robot dynamics allows extra measures, such as energy efficiency, to be optimised alongside maximising the likelihood of intercepting the target. We derive a statistical model for a vision system and a Lagrangian dynamical model of a robotic arm, showing how to relate joint torques to the vision. The method is tested by applying it to the problem of catching a simulated moving object.</description><subject>Cameras</subject><subject>Equations</subject><subject>Joints</subject><subject>Mathematical model</subject><subject>Robot kinematics</subject><subject>Trajectory</subject><issn>2153-0858</issn><issn>2153-0866</issn><isbn>9781424466740</isbn><isbn>1424466741</isbn><isbn>9781424466764</isbn><isbn>1424466768</isbn><isbn>142446675X</isbn><isbn>9781424466757</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVUNtKAzEUjDew1P0A8WV_IDXJObn5JsVLoVCw-lyymyxG9iKbVdi_N2ARfBqGYYaZIeSasxXnzN5uXnb7lWCZSoXGgDghhdWGo0BUSis8JQvBJVBmlDr7pyE7_9OkuSRFSh-M5ShtjVULcref3BTTFGvXlt8xfbmW-rl3XazLbvChLZthLN9d72mYQ1kPw-hjny1Df0UuGtemUBxxSd4eH17Xz3S7e9qs77c0ci0nWkGTq1fBAFNMaKykd3kUNAFBS9ComMWAzPkKgjIocjfNoalqh0ZZAUty85sbQwiHzzF2bpwPxyfgB7OqS84</recordid><startdate>201010</startdate><enddate>201010</enddate><creator>Beale, D</creator><creator>Iravani, P</creator><creator>Hall, P</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201010</creationdate><title>Statistical visual-dynamic model for hand-eye coordination</title><author>Beale, D ; Iravani, P ; Hall, P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-b3f201be83060274b5da1093fe43753746094e40adb3e6842107713fbca486923</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Cameras</topic><topic>Equations</topic><topic>Joints</topic><topic>Mathematical model</topic><topic>Robot kinematics</topic><topic>Trajectory</topic><toplevel>online_resources</toplevel><creatorcontrib>Beale, D</creatorcontrib><creatorcontrib>Iravani, P</creatorcontrib><creatorcontrib>Hall, P</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Beale, D</au><au>Iravani, P</au><au>Hall, P</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Statistical visual-dynamic model for hand-eye coordination</atitle><btitle>2010 IEEE/RSJ International Conference on Intelligent Robots and Systems</btitle><stitle>IROS</stitle><date>2010-10</date><risdate>2010</risdate><spage>3931</spage><epage>3936</epage><pages>3931-3936</pages><issn>2153-0858</issn><eissn>2153-0866</eissn><isbn>9781424466740</isbn><isbn>1424466741</isbn><eisbn>9781424466764</eisbn><eisbn>1424466768</eisbn><eisbn>142446675X</eisbn><eisbn>9781424466757</eisbn><abstract>This paper introduces a new statistical method for combining vision and robot dynamics to generate trajectories to intercept a moving object. Previous methods only use information from the kinematics without considering the forces needed to move along the trajectory. Using robot dynamics allows extra measures, such as energy efficiency, to be optimised alongside maximising the likelihood of intercepting the target. We derive a statistical model for a vision system and a Lagrangian dynamical model of a robotic arm, showing how to relate joint torques to the vision. The method is tested by applying it to the problem of catching a simulated moving object.</abstract><pub>IEEE</pub><doi>10.1109/IROS.2010.5648832</doi><tpages>6</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cameras Equations Joints Mathematical model Robot kinematics Trajectory |
| title | Statistical visual-dynamic model for hand-eye coordination |
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