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题名: BP networks based trajectory planning and inverse kinematics of a reconfigurable Mars rover
作者: Zhang LP(张力平) ; Ma SG(马书根) ; Li B(李斌) ; Zhang Z(张政) ; Zhang GW(张国伟) ; Cao BG(曹秉刚)
作者部门: 机器人学研究室
会议名称: 2nd International Symposium on Neural Networks
会议日期: May 30-June 1, 2005
会议地点: Chongqing, China
会议主办者: Chongqing Univ, SW Normal Univ, Chongqing Univ, Posts& Telecommun, SW Agr Univ, Chongqing Educ Coll, Chinese Univ Hong Kong, Asia Pacific Neural Network Assembly, European Neural Network Soc, IEEE Circuits & Syst Soc, IEEE Computat Intelligence Soc, Natl Nat Sci Fdn China, K C Wong Educ Fdn Hong Kong
会议录: ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS
会议录出版者: SPRINGER-VERLAG
会议录出版地: BERLIN
出版日期: 2005
页码: 247-252
收录类别: SCI ; CPCI(ISTP) ; EI
ISSN号: 0302-9743
ISBN号: 3-540-25914-7
摘要: The inverse kinematics of series manipulators presents an inherent complexity due to their various structures and kinematics constraints. To a novel reconfigurable Mars rover's arm, the inverse kinematics had been solved by numerical method combined with space geometry relations, but the complex calculating process can not be utilized in real-time control. In this paper, some actions in common use are programmed in the child rover, and the BP neural network was used to solve the inverse kinematics and trajectory planning. To a desired trajectory, some solutions by direct kinematics algorithms and geometry relations corresponding to the trajectory were used as the BP network's training data set, and the non-linear mapping from joint-variable space to operation-variable space was obtained with iterative training and learning method. The results show the output of training is consistent with the desired path, and the obtained reference trajectory is smooth.
语种: 英语
产权排序: 2
WOS记录号: WOS:000230167700039
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8599
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
张力平; 马书根; 李斌; 张政; 张国伟; 曹秉刚.BP networks based trajectory planning and inverse kinematics of a reconfigurable Mars rover.见:SPRINGER-VERLAG.ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS,BERLIN,2005,247-252
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