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题名: Neural network based kinematic control of the hyper-redundant snake-like manipulator
作者: Liu JG(刘金国) ; Wang YC(王越超) ; Li B(李斌) ; Ma SG(马书根)
作者部门: 机器人学研究室
会议名称: 4th International Symposium on Neural Networks (ISNN 2007)
会议日期: June 3-7, 2007
会议地点: Nanjing, China
会议主办者: Natl Nat Sci Fdn China, KC Wong Educ Fdn, SE Univ China, Chinese Univ Hong Kong, Univ Illinois, Chicago
会议录: Advances in Neural Networks - ISNN 2007, Pt 1, Proceedings
会议录出版者: SPRINGER-VERLAG
会议录出版地: BERLIN
出版日期: 2007
页码: 767-775
收录类别: CPCI(ISTP) ; EI
ISSN号: 0302-9743
ISBN号: 978-3-540-72382-0
摘要: In a sinusoid like curve configuration, the snake-like manipulator (also called snake arm) has a wide range of potential applications for its redundancy to overcome conventional industrial robot's limitation when carrying out a complex task. It can perform many kinds of locomotion like the nature snake or the animal's tentacle to avoid obstacles, follow designated trajectories, and grasp objects. Effectively control of the snake-like manipulator is difficult for its redundancy. In this study, we propose an approach based on BP neural network to kinematic control the hyper-redundant snake-like manipulator. This approach, inspired by the Serpenoid curve and the concertina motion principle of the nature snake, is completely capable of solving the control problem of a planar snake-like manipulator with any number of links following any desired direction and trajectory. With shape transformation and base rotation, the manipulator's configuration changes accordingly and moves actively to perform the designated tasks. By using BP neural networks in modeling the inverse kinematics, this approach has such superiorities as few control parameters and high precision. Simulations have demonstrated that this control technique for the snake-like manipulator is available and effective.
语种: 英语
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8804
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
刘金国; 王越超; 李斌; 马书根.Neural network based kinematic control of the hyper-redundant snake-like manipulator.见:SPRINGER-VERLAG.Advances in Neural Networks - ISNN 2007, Pt 1, Proceedings,BERLIN,2007,767-775
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