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Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization
In this study, a new method of smooth path planning is proposed based on Bezier curves and is applied to solve the problem of redundant nodes and peak inflection points in the path planning process of traditional algorithms. First, genetic operations are used to obtain the control points of the Bezi...
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| Published in: | Computational intelligence and neuroscience 2020, Vol.2020 (2020), p.1-10 |
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| cites | cdi_FETCH-LOGICAL-c499t-16bbe1d34936d82f669b92fe336ac6cea1b741880a014aa65387bc7dd1abd55d3 |
| container_end_page | 10 |
| container_issue | 2020 |
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| container_title | Computational intelligence and neuroscience |
| container_volume | 2020 |
| creator | Wang, Lin Zang, Shaofei Liu, Yang Ma, Jianwei |
| description | In this study, a new method of smooth path planning is proposed based on Bezier curves and is applied to solve the problem of redundant nodes and peak inflection points in the path planning process of traditional algorithms. First, genetic operations are used to obtain the control points of the Bezier curve. Second, a shorter path is selected by an optimization criterion that the length of the Bezier curve is determined by the control points. Finally, a safe distance and adaptive penalty factor are introduced into the fitness function to ensure the safety of the walking process of the robot. Numerous experiments are implemented in two different environments and compared with the existing methods. It is proved that the proposed method is more effective to generate a shorter, smoother, and safer path compared with traditional approaches. |
| doi_str_mv | 10.1155/2020/9813040 |
| format | article |
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It is proved that the proposed method is more effective to generate a shorter, smoother, and safer path compared with traditional approaches.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2020/9813040</identifier><identifier>PMID: 32184811</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Adaptive control ; Algorithms ; Computer Simulation ; Curves ; Genetic algorithms ; Inflection points ; Methods ; Mutation ; Optimization ; Path planning ; Planning ; Robotics - methods ; Robots ; Walking</subject><ispartof>Computational intelligence and neuroscience, 2020, Vol.2020 (2020), p.1-10</ispartof><rights>Copyright © 2020 Jianwei Ma et al.</rights><rights>COPYRIGHT 2020 John Wiley & Sons, Inc.</rights><rights>Copyright © 2020 Jianwei Ma et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2020 Jianwei Ma et al. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-16bbe1d34936d82f669b92fe336ac6cea1b741880a014aa65387bc7dd1abd55d3</citedby><cites>FETCH-LOGICAL-c499t-16bbe1d34936d82f669b92fe336ac6cea1b741880a014aa65387bc7dd1abd55d3</cites><orcidid>0000-0002-3905-0115</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2373990499/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2373990499?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,4010,25731,27900,27901,27902,36989,36990,44566,74869</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32184811$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Köker, Raşit</contributor><contributor>Raşit Köker</contributor><creatorcontrib>Wang, Lin</creatorcontrib><creatorcontrib>Zang, Shaofei</creatorcontrib><creatorcontrib>Liu, Yang</creatorcontrib><creatorcontrib>Ma, Jianwei</creatorcontrib><title>Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization</title><title>Computational intelligence and neuroscience</title><addtitle>Comput Intell Neurosci</addtitle><description>In this study, a new method of smooth path planning is proposed based on Bezier curves and is applied to solve the problem of redundant nodes and peak inflection points in the path planning process of traditional algorithms. 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It is proved that the proposed method is more effective to generate a shorter, smoother, and safer path compared with traditional approaches.</description><subject>Adaptive control</subject><subject>Algorithms</subject><subject>Computer Simulation</subject><subject>Curves</subject><subject>Genetic algorithms</subject><subject>Inflection points</subject><subject>Methods</subject><subject>Mutation</subject><subject>Optimization</subject><subject>Path planning</subject><subject>Planning</subject><subject>Robotics - methods</subject><subject>Robots</subject><subject>Walking</subject><issn>1687-5265</issn><issn>1687-5273</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqNkc1rFDEYh4NYbLt68ywBL0K7Nh-Tr4uwXWwrFFpEwVvITDK7KTPJNpOx2L_eDLvdqidPeeF9eJJffgC8xegjxoydEUTQmZKYogq9AEeYSzFnRNCX-5mzQ3A8DHcIMcEQeQUOKcGykhgfgR9fYx0zvDV5DW87E4IPK3huBmdhDPDSBZd9AxfdKiaf1z28GKfVQ5nhMobswxjHAZ67R-8SvNlk3_tHk30Mr8FBa7rBvdmdM_D94vO35dX8-ubyy3JxPW8qpfIc87p22NJKUW4laTlXtSKto5SbhjfO4FpUWEpkEK6M4YxKUTfCWmxqy5ilM_Bp692Mde9s40JOptOb5HuTfulovP57E_xar-JPLRBHkqsi-LATpHg_uiHr3g-N68pnuJJNEyqkFBJzVND3_6B3cUyhxJsoqhQqmZ6plemc9qGN5d5mkuoFJ0QQTEpbM3C6pZoUhyG5dv9kjPRUrJ6K1btiC_7uz5h7-KnJApxsgbUP1jz4_9S5wrjWPNOYSiUJ_Q1ZErP2</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Wang, Lin</creator><creator>Zang, Shaofei</creator><creator>Liu, Yang</creator><creator>Ma, Jianwei</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>8AL</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3905-0115</orcidid></search><sort><creationdate>2020</creationdate><title>Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization</title><author>Wang, Lin ; Zang, Shaofei ; Liu, Yang ; Ma, Jianwei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c499t-16bbe1d34936d82f669b92fe336ac6cea1b741880a014aa65387bc7dd1abd55d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adaptive control</topic><topic>Algorithms</topic><topic>Computer Simulation</topic><topic>Curves</topic><topic>Genetic algorithms</topic><topic>Inflection points</topic><topic>Methods</topic><topic>Mutation</topic><topic>Optimization</topic><topic>Path planning</topic><topic>Planning</topic><topic>Robotics - 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| source | Wiley Online Library Open Access; ProQuest - Publicly Available Content Database |
| subjects | Adaptive control Algorithms Computer Simulation Curves Genetic algorithms Inflection points Methods Mutation Optimization Path planning Planning Robotics - methods Robots Walking |
| title | Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization |
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