| A Rough Set GA-based Hybrid Method for Robot Path Planning |
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| 作者姓名： | Cheng-Dong Wu Ying Zhang Meng-Xin Li Shenyang Jianzhu University Shenyang PRC Yong Yue University of Luton Luton LU JU UK |
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| 作者单位： | Cheng-Dong Wu，Ying Zhang，Meng-Xin Li Shenyang Jianzhu University，Shenyang 110168，PRC Yong Yue University of Luton，Luton LU1 3JU，UK |
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| 基金项目： | This project is partially supported by Science Research Funding from the Education Department of Liaoning Province, China (No.J9906065). |
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| 摘 要： | In this paper, a hybrid method based on rough sets and genetic algorithms, is proposed to improve the speed of robot path planning. Decision rules are obtained using rough set theory. A series of available paths are produced by training obtained minimal decision rules. Path populations axe optimised by using genetic algorithms until the best path is obtained. Experiment results show that this hybrid method is capable of improving robot path planning speed.
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| 收稿时间： | 15 February 2005 |
| 修稿时间： | 2005-9-30 |
A Rough Set GA-based Hybrid Method for Robot Path Planning |
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| Cheng-Dong Wu,Ying Zhang,Meng-Xin Li Shenyang Jianzhu University,Shenyang ,PRC Yong Yue University of Luton,Luton LU JU,UK.A Rough Set GA-based Hybrid Method for Robot Path Planning[J].International Journal of Automation and computing,2006,3(1):29-34. |
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| Authors: | Cheng-Dong Wu Ying Zhang Meng-Xin Li Yong Yue |
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| Affiliation: | (1) Shenyang Jianzhu University, Shenyang, 110168, PRC;(2) University of Luton, Luton, LU1 3JU, UK |
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| Abstract: | In this paper, a hybrid method based on rough sets and genetic algorithms, is proposed to improve the speed of robot path planning. Decision rules are obtained using rough set theory. A series of available paths are produced by training obtained minimal decision rules. Path populations axe optimised by using genetic algorithms until the best path is obtained. Experiment results show that this hybrid method is capable of improving robot path planning speed. |
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| Keywords: | Rough sets genetic algorithms robot path planning |
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