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An optimization algorithm with novel RFA-PSO cooperative evolution: Applications to parameter decision of a snake robot
Gao Q(高琴); Wang ZL(王哲龙); Li HY(李洪谊)
作者部门机器人学研究室
关键词Particle Swarm Optimization Human Activity Recognition Hybrid Genetic Algorithm Cpg-based Locomotion Kinematics Analysis Design System Classification Adaptation Networks
发表期刊Mathematical Problems in Engineering
ISSN1024-123X
2015
卷号2015页码:1-12
收录类别SCI ; EI
EI收录号20152400933509
WOS记录号WOS:000356283700001
产权排序1
资助机构State Key Laboratory of Robotics, Shenyang Institute of Automation ; National Natural Science Foundation of China [61174027] ; National High Technology Research and Development Program [2012AA04150502]
摘要The success to design a hybrid optimization algorithm depends on how to make full use of the effect of exploration and exploitation carried by agents. To improve the exploration and exploitation property of the agents, we present a hybrid optimization algorithm with both local and global search capabilities by combining the global search property of rain forest algorithm (RFA) and the rapid convergence of PSO. Originally two kinds of agents, RFAAs and PSOAs, are introduced to carry out exploration and exploitation, respectively. In order to improve population diversification, uniform distribution and adaptive range division are carried out by RFAAs in flexible scale during the iteration. A further improvement has been provided to enhance the convergence rate and processing speed by combining PSO algorithm with potential guides found by both RFAAs and PSOAs. Since several contingent local minima conditions may happen to PSO, special agent transformation is suggested to provide information exchanging and cooperative coevolution between RFAAs and PSOAs. Effectiveness and efficiency of the proposed algorithm are compared with several algorithms in the various benchmark function problems. Finally, engineering design optimization problems taken from the gait control of a snake-like robot are implemented successfully by the proposed RFA-PSO.
语种英语
WOS标题词Science & Technology ; Technology ; Physical Sciences
WOS类目Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
关键词[WOS]PARTICLE SWARM OPTIMIZATION ; HUMAN ACTIVITY RECOGNITION ; HYBRID GENETIC ALGORITHM ; CPG-BASED LOCOMOTION ; KINEMATICS ANALYSIS ; DESIGN ; SYSTEM ; CLASSIFICATION ; ADAPTATION ; NETWORKS
WOS研究方向Engineering ; Mathematics
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文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/16229
专题机器人学研究室
通讯作者Gao Q(高琴)
作者单位1.School of Control Science and Engineering, Dalian University of Technology, Dalian, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
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GB/T 7714
Gao Q,Wang ZL,Li HY. An optimization algorithm with novel RFA-PSO cooperative evolution: Applications to parameter decision of a snake robot[J]. Mathematical Problems in Engineering,2015,2015:1-12.
APA Gao Q,Wang ZL,&Li HY.(2015).An optimization algorithm with novel RFA-PSO cooperative evolution: Applications to parameter decision of a snake robot.Mathematical Problems in Engineering,2015,1-12.
MLA Gao Q,et al."An optimization algorithm with novel RFA-PSO cooperative evolution: Applications to parameter decision of a snake robot".Mathematical Problems in Engineering 2015(2015):1-12.
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