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Robot planning with artificial potential field guided ant colony optimization algorithm
Zhao, Dongbin; Yi, Jianqiang; Jiao, L; Wang, L; Gao, X; Liu, J; Wu, F
刊名ADVANCES IN NATURAL COMPUTATION, PT 2
2006
卷号4222页码:222-231
英文摘要This paper investigates the problem of robot planning with ant colony optimization and artificial potential filed algorithms. Robot planning is to find a feasible path from a source to a goal while avoiding obstacles in configuration space. Artificial potential field (APF) is verified as an efficient method to find a path by following the maximum potential field gradient. But it suffers from the local minima. However, ant colony optimization (ACO) is characterized as powerful probabilistic search ability, which is thought to be fit for solving such local minima problems. By the combination of both merits, an APF guided ACO algorithm is proposed, which shows some good features in searching for the optimal path solution. The length optimal path solution can always be achieved with the proposed hybrid algorithm in different obstacles environment from simulation results.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
研究领域[WOS]Computer Science
关键词[WOS]TIME OBSTACLE AVOIDANCE
收录类别ISTP ; SCI
语种英语
WOS记录号WOS:000241892100028
公开日期2015-12-24
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/9227]  
专题自动化研究所_09年以前成果
作者单位Chinese Acad Sci, Lab Complex Syst & Intelligence Sci, Inst Automat, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714
Zhao, Dongbin,Yi, Jianqiang,Jiao, L,et al. Robot planning with artificial potential field guided ant colony optimization algorithm[J]. ADVANCES IN NATURAL COMPUTATION, PT 2,2006,4222:222-231.
APA Zhao, Dongbin.,Yi, Jianqiang.,Jiao, L.,Wang, L.,Gao, X.,...&Wu, F.(2006).Robot planning with artificial potential field guided ant colony optimization algorithm.ADVANCES IN NATURAL COMPUTATION, PT 2,4222,222-231.
MLA Zhao, Dongbin,et al."Robot planning with artificial potential field guided ant colony optimization algorithm".ADVANCES IN NATURAL COMPUTATION, PT 2 4222(2006):222-231.
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