Rbf neural network based shape control of hyper-redundant with constrained end-effector
文献类型：期刊论文
| 作者 | Liu, Jinguo; Wang, Yuechao; Ma, Shugen; Li, Bin |
| 刊名 | Advances in neural networks - isnn 2006, pt 2, proceedings
 |
| 出版日期 | 2006 |
| 卷号 | 3972页码:1146-1152 |
| ISSN号 | 0302-9743 |
| 通讯作者 | Liu, jinguo(liujinguo@sia.cn) |
| 英文摘要 | Hyper-redundant manipulator has more degrees of freedom than the least necessary to perform a given task, thus it has the features of overcoming conventional industrial robot's limitation to carry out a designated difficult task. when the manipulator carries out the missions such as brushing or writing on a surface, drilling or inspection in a hole, the end-effector of the manipulator usually has both position and orientation requirement. effective control of the byper-redundant manipulator with such constrained end-effector is difficult for its redundancy. in this paper, a novel approach based on rbf neural network has been proposed to kinematically control the hyper-redundant manipulator. this technique, using variable regular polygon and rbf neural networks models, is completely capable of solving the control problem of a planar hyper-redundant manipulator with any number of links following any desired direction and path. with the shape transformation of variable regular polygon, the manipulator's configuration changes accordingly and moves actively to perform the tasks. compared with other methods to our knowledge, this technique has such superiorities as fewer control parameters and higher precision. simulations have demonstrated that this control technique is available and effective. |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods |
| 语种 | 英语 |
| WOS记录号 | WOS:000239483000168 |
| 出版者 | SPRINGER-VERLAG BERLIN |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2379867 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Liu, Jinguo |
| 作者单位 | 1.Chinese Acad Sci, Robot Lab, Shenyang Inst Automat, Shenyang 110016, Peoples R China 2.Ritsumeikan Univ, COE Res Inst, Shiga 5258577, Japan 3.Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Jinguo,Wang, Yuechao,Ma, Shugen,et al. Rbf neural network based shape control of hyper-redundant with constrained end-effector[J]. Advances in neural networks - isnn 2006, pt 2, proceedings,2006,3972:1146-1152. |
| APA | Liu, Jinguo,Wang, Yuechao,Ma, Shugen,&Li, Bin.(2006).Rbf neural network based shape control of hyper-redundant with constrained end-effector.Advances in neural networks - isnn 2006, pt 2, proceedings,3972,1146-1152. |
| MLA | Liu, Jinguo,et al."Rbf neural network based shape control of hyper-redundant with constrained end-effector".Advances in neural networks - isnn 2006, pt 2, proceedings 3972(2006):1146-1152. |
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来源：中国科学院大学
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