Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot
TP242.6; Presents the mobile robots dynamic motion planning problem with a task to find an obstacle-free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optim...
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| Veröffentlicht in: | 哈尔滨工业大学学报(英文版) 2001-09, Vol.8 (3), p.228-232 |
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| container_title | 哈尔滨工业大学学报(英文版) |
| container_volume | 8 |
| creator | WANG Yue-hai HONG Bing-rong |
| description | TP242.6; Presents the mobile robots dynamic motion planning problem with a task to find an obstacle-free route
that requires minimum travel time from the start point to the destination point in a changing environment, due to
the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optimal approach proposed to find any
obstacle-free path and the GA used to select the optimal one, points ont that using this learned knowledge off
line, a mobile robot can navigate to its goal point when it faces new scenario on-line. Concludes with the opti
mal rule base given and the simulation results showing its effectiveness. |
| format | Article |
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that requires minimum travel time from the start point to the destination point in a changing environment, due to
the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optimal approach proposed to find any
obstacle-free path and the GA used to select the optimal one, points ont that using this learned knowledge off
line, a mobile robot can navigate to its goal point when it faces new scenario on-line. Concludes with the opti
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that requires minimum travel time from the start point to the destination point in a changing environment, due to
the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optimal approach proposed to find any
obstacle-free path and the GA used to select the optimal one, points ont that using this learned knowledge off
line, a mobile robot can navigate to its goal point when it faces new scenario on-line. Concludes with the opti
mal rule base given and the simulation results showing its effectiveness.</description><issn>1005-9113</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><recordid>eNotjctKw0AUQGehYK3-w3yAgXtn8phZStEqFETQdbjzSlKSmZCk2PTrLejqLA6cc8M2CFBkGlHesft5PgJIraHcsM-9j37pLKe-SVO3tEMWTpfLyg3N3nG3RhqudkhLlyIfe4qxiw2ncZwS2ZaHNHG6atP1nk_JpOWB3QbqZ__4zy37fn352r1lh4_9--75kM0IRZWFwtjc-UJLTVrkAq1CpUp0VuSlUJWzMpAuK4MGfS4kCaOEwsqBDUGAl1v29Nf9oRgoNvUxnaZ4PdatN83qzmdTewGAIAEq-Qu2jE44</recordid><startdate>200109</startdate><enddate>200109</enddate><creator>WANG Yue-hai</creator><creator>HONG Bing-rong</creator><general>Dept. of Computer Science Engineering, Harbin Institute of Technology</general><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>200109</creationdate><title>Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot</title><author>WANG Yue-hai ; HONG Bing-rong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-s1057-f5bc4de5939a92421c818861dc246287dc3fa967b1b1e423a2b82817d0cff20e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>WANG Yue-hai</creatorcontrib><creatorcontrib>HONG Bing-rong</creatorcontrib><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>哈尔滨工业大学学报(英文版)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>WANG Yue-hai</au><au>HONG Bing-rong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot</atitle><jtitle>哈尔滨工业大学学报(英文版)</jtitle><date>2001-09</date><risdate>2001</risdate><volume>8</volume><issue>3</issue><spage>228</spage><epage>232</epage><pages>228-232</pages><issn>1005-9113</issn><abstract>TP242.6; Presents the mobile robots dynamic motion planning problem with a task to find an obstacle-free route
that requires minimum travel time from the start point to the destination point in a changing environment, due to
the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optimal approach proposed to find any
obstacle-free path and the GA used to select the optimal one, points ont that using this learned knowledge off
line, a mobile robot can navigate to its goal point when it faces new scenario on-line. Concludes with the opti
mal rule base given and the simulation results showing its effectiveness.</abstract><pub>Dept. of Computer Science Engineering, Harbin Institute of Technology</pub><tpages>5</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1005-9113 |
| ispartof | 哈尔滨工业大学学报(英文版), 2001-09, Vol.8 (3), p.228-232 |
| issn | 1005-9113 |
| language | eng |
| recordid | cdi_wanfang_journals_hebgydxxb_e200103007 |
| source | Alma/SFX Local Collection |
| title | Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot |
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