Evolving composite robot behaviour - a modular architecture
We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive...
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| creator | Larsen, T. Hansen, S.T. |
| description | We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system. |
| doi_str_mv | 10.1109/ROMOCO.2005.201435 |
| format | Conference Proceeding |
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The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system.</description><subject>Automatic control</subject><subject>Computational modeling</subject><subject>Computer science</subject><subject>Computer simulation</subject><subject>Control systems</subject><subject>Evolutionary computation</subject><subject>Neural networks</subject><subject>Robot control</subject><subject>Robot sensing systems</subject><subject>Robotics and automation</subject><isbn>9788371432668</isbn><isbn>8371432666</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT9tKw0AUXBBBqfmB-rI_kLr3bPBJQr1AJSD2uZxsz9qVxC2bC_j3Lth5mGFgGGYIWXO24ZzVDx_te9u0G8GYzsSV1FekqCtrZZWNMMbekGIcv1mGrI2Q-pY8bpfYL-Hni7o4nOMYJqQpdnGiHZ5gCXFOtKRAh3ice0gUkjvljJvmhHfk2kM_YnHRFdk_bz-b13LXvrw1T7sy8EpPpUGrrUfjTC0RrPOdEixbYawX0gCYjvPagueoJctjnTReMcudPnYWKrki9_-9AREP5xQGSL8HrrVS-dcffw5HGA</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Larsen, T.</creator><creator>Hansen, S.T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2005</creationdate><title>Evolving composite robot behaviour - a modular architecture</title><author>Larsen, T. ; Hansen, S.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-6e858fe6c693ea8cfb420e6c268f236aa6b1198af1e530837c36f4081c5db8a73</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Automatic control</topic><topic>Computational modeling</topic><topic>Computer science</topic><topic>Computer simulation</topic><topic>Control systems</topic><topic>Evolutionary computation</topic><topic>Neural networks</topic><topic>Robot control</topic><topic>Robot sensing systems</topic><topic>Robotics and automation</topic><toplevel>online_resources</toplevel><creatorcontrib>Larsen, T.</creatorcontrib><creatorcontrib>Hansen, S.T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Larsen, T.</au><au>Hansen, S.T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Evolving composite robot behaviour - a modular architecture</atitle><btitle>Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05</btitle><stitle>ROMOCO</stitle><date>2005</date><risdate>2005</risdate><spage>271</spage><epage>276</epage><pages>271-276</pages><isbn>9788371432668</isbn><isbn>8371432666</isbn><abstract>We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system.</abstract><pub>IEEE</pub><doi>10.1109/ROMOCO.2005.201435</doi><tpages>6</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Automatic control Computational modeling Computer science Computer simulation Control systems Evolutionary computation Neural networks Robot control Robot sensing systems Robotics and automation |
| title | Evolving composite robot behaviour - a modular architecture |
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