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Non-holonomic path planning using a quasi-random PRM approach
The aim of this article is to compare experimentally the use of quasi-random sampling techniques for nonholonomic path planning. The experiments are evaluated in the context of the probabilistic roadmap methods (PRM). Two quasi-random variants of PRM-based planners are proposed: (1) a classical PRM...
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creator | Sanchez, A. Arenas, J.A. Zapata, R. |
description | The aim of this article is to compare experimentally the use of quasi-random sampling techniques for nonholonomic path planning. The experiments are evaluated in the context of the probabilistic roadmap methods (PRM). Two quasi-random variants of PRM-based planners are proposed: (1) a classical PRM with quasi-random sampling, and (2) a quasi-random lazy-PRM. Both have been implemented for car-like robots, and are shown through experimental results to offer some performance advantages in comparison to their randomized counterparts. |
doi_str_mv | 10.1109/IRDS.2002.1041611 |
format | conference_proceeding |
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The experiments are evaluated in the context of the probabilistic roadmap methods (PRM). Two quasi-random variants of PRM-based planners are proposed: (1) a classical PRM with quasi-random sampling, and (2) a quasi-random lazy-PRM. Both have been implemented for car-like robots, and are shown through experimental results to offer some performance advantages in comparison to their randomized counterparts.</description><identifier>ISBN: 0780373987</identifier><identifier>ISBN: 9780780373983</identifier><identifier>DOI: 10.1109/IRDS.2002.1041611</identifier><language>eng</language><publisher>Piscataway NJ: IEEE</publisher><subject>Algorithm design and analysis ; Applied sciences ; Artificial intelligence ; Computer science ; Computer science; control theory; systems ; Control theory. Systems ; Exact sciences and technology ; Motion planning ; Orbital robotics ; Path planning ; Pattern recognition. Digital image processing. Computational geometry ; Programmable control ; Road accidents ; Robot sensing systems ; Robotics ; Robustness ; Sampling methods</subject><ispartof>IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002, Vol.3, p.2305-2310 vol.3</ispartof><rights>2004 INIST-CNRS</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1041611$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1041611$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15671966$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Sanchez, A.</creatorcontrib><creatorcontrib>Arenas, J.A.</creatorcontrib><creatorcontrib>Zapata, R.</creatorcontrib><title>Non-holonomic path planning using a quasi-random PRM approach</title><title>IEEE/RSJ International Conference on Intelligent Robots and Systems</title><addtitle>IRDS</addtitle><description>The aim of this article is to compare experimentally the use of quasi-random sampling techniques for nonholonomic path planning. The experiments are evaluated in the context of the probabilistic roadmap methods (PRM). Two quasi-random variants of PRM-based planners are proposed: (1) a classical PRM with quasi-random sampling, and (2) a quasi-random lazy-PRM. Both have been implemented for car-like robots, and are shown through experimental results to offer some performance advantages in comparison to their randomized counterparts.</description><subject>Algorithm design and analysis</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Exact sciences and technology</subject><subject>Motion planning</subject><subject>Orbital robotics</subject><subject>Path planning</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Programmable control</subject><subject>Road accidents</subject><subject>Robot sensing systems</subject><subject>Robotics</subject><subject>Robustness</subject><subject>Sampling methods</subject><isbn>0780373987</isbn><isbn>9780780373983</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2002</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFULlOw0AUXAkhASEfgGjcUNq85728BQUKV6RwKEAdPW_WeJGPxZsU_D1GRmKKmWJGo9EwdoaQIYK5XK5vXrMcIM8QBCrEA3YCugCuuSn0EZvH-AkjhJDcmGN29dR3ad03fde33iaBdnUSGuo6330k-_jLlHztKfp0oG7bt8nL-jGhEIaebH3KDitqopv_6Yy9392-LR7S1fP9cnG9SmvUuEuVJe6MzVXOHQqoKpBU5kaBFIqjc4KXUOpCuhKdsIUsbF5shSRpnCiNtnzGLqbeQNFSU41TrI-bMPiWhu8NSqXRKDXmzqecd87929MT_Ae3t1Kk</recordid><startdate>2002</startdate><enddate>2002</enddate><creator>Sanchez, A.</creator><creator>Arenas, J.A.</creator><creator>Zapata, R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>IQODW</scope></search><sort><creationdate>2002</creationdate><title>Non-holonomic path planning using a quasi-random PRM approach</title><author>Sanchez, A. ; Arenas, J.A. ; Zapata, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-h171t-6ca3e9c2623e140ff05ab296054631ee43b0b785eb1e4c858c28d45a59e4b97c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Algorithm design and analysis</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Exact sciences and technology</topic><topic>Motion planning</topic><topic>Orbital robotics</topic><topic>Path planning</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Programmable control</topic><topic>Road accidents</topic><topic>Robot sensing systems</topic><topic>Robotics</topic><topic>Robustness</topic><topic>Sampling methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Sanchez, A.</creatorcontrib><creatorcontrib>Arenas, J.A.</creatorcontrib><creatorcontrib>Zapata, R.</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/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sanchez, A.</au><au>Arenas, J.A.</au><au>Zapata, R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Non-holonomic path planning using a quasi-random PRM approach</atitle><btitle>IEEE/RSJ International Conference on Intelligent Robots and Systems</btitle><stitle>IRDS</stitle><date>2002</date><risdate>2002</risdate><volume>3</volume><spage>2305</spage><epage>2310 vol.3</epage><pages>2305-2310 vol.3</pages><isbn>0780373987</isbn><isbn>9780780373983</isbn><abstract>The aim of this article is to compare experimentally the use of quasi-random sampling techniques for nonholonomic path planning. The experiments are evaluated in the context of the probabilistic roadmap methods (PRM). Two quasi-random variants of PRM-based planners are proposed: (1) a classical PRM with quasi-random sampling, and (2) a quasi-random lazy-PRM. Both have been implemented for car-like robots, and are shown through experimental results to offer some performance advantages in comparison to their randomized counterparts.</abstract><cop>Piscataway NJ</cop><pub>IEEE</pub><doi>10.1109/IRDS.2002.1041611</doi><tpages>6</tpages></addata></record> |
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subjects | Algorithm design and analysis Applied sciences Artificial intelligence Computer science Computer science control theory systems Control theory. Systems Exact sciences and technology Motion planning Orbital robotics Path planning Pattern recognition. Digital image processing. Computational geometry Programmable control Road accidents Robot sensing systems Robotics Robustness Sampling methods |
title | Non-holonomic path planning using a quasi-random PRM approach |
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