中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Motion planning for climbing robot based on hybrid navigation

文献类型:期刊论文

作者Jiang, Yong; Wang, Hongguang; Fang, Lijin; Zhao, Mingyang
刊名Advances in machine learning and cybernetics
出版日期2006
卷号3930页码:91-100
ISSN号0302-9743
通讯作者Jiang, yong(jiangyong@sia.cn)
英文摘要In this paper, a motion planning method for autonomous control of a bipedal climbing robot based on hybrid navigation is presented. the algorithm of hybrid navigation blends the optimality of the trajectory planning with the capabilities in expressing knowledge and learning of the fuzzy neural network. the real task environment of the climbing robot is both known and dynamic. therefore the trajectory planning is used to search roughly for the optimal trajectories which will lead towards the goal according to prior data. meanwhile, by the process of the multi-sensor data fusion, the fuzzy neural network is employed in dealing efficiently with the uncertain and dynamic situations. the properties of motion planning based on the hybrid navigation are verified by the computer simulations and experiments.
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Cybernetics ; Computer Science, Information Systems
语种英语
WOS记录号WOS:000238282100010
出版者SPRINGER-VERLAG BERLIN
URI标识http://www.irgrid.ac.cn/handle/1471x/2379061
专题中国科学院大学
通讯作者Jiang, Yong
作者单位1.Chinese Acad Sci, Shenyang Inst Automat, Robot Lab, Shenyang 110016, Peoples R China
2.Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China
推荐引用方式
GB/T 7714
Jiang, Yong,Wang, Hongguang,Fang, Lijin,et al. Motion planning for climbing robot based on hybrid navigation[J]. Advances in machine learning and cybernetics,2006,3930:91-100.
APA Jiang, Yong,Wang, Hongguang,Fang, Lijin,&Zhao, Mingyang.(2006).Motion planning for climbing robot based on hybrid navigation.Advances in machine learning and cybernetics,3930,91-100.
MLA Jiang, Yong,et al."Motion planning for climbing robot based on hybrid navigation".Advances in machine learning and cybernetics 3930(2006):91-100.

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来源:中国科学院大学

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