Novel power-exponent-type modified RNN for RMP scheme of redundant manipulators with noise and physical constraints | |
Tong YC(佟玉闯)1,2,3; Liu JG(刘金国)2,3 | |
刊名 | Neurocomputing |
2022 | |
卷号 | 467页码:266-281 |
关键词 | Redundant manipulator Repetitive motion planning Recurrent neural network Noise Physical constraint |
ISSN号 | 0925-2312 |
产权排序 | 1 |
英文摘要 | Noise and physical constraints of redundant manipulators are the two major challenges in the repetitive motion planning (RMP) problems. Therefore, this paper proposed a power-exponent-type modified recurrent neural network (PET-MRNN) to simultaneously address both noise and physical constraints. Moreover, PET-MRNN model is activated by a new Sbp-sinh type nonlinear activation function proposed in this paper. The Sbp-sinh type activation function is first applied to such time varying quadratic program (TVQP) solving and possesses excellent convergence performance. Theoretical analysis proves that the PET-MRNN model can completely eliminate noise disturbance through learning and compensation during the convergence process, and then converge the residual error to zero and obtain the theoretical solution. Finally, simulation and experiments further proved the superiority of the PET-MRNN and the Sbp-sinh type activation function. |
语种 | 英语 |
WOS记录号 | WOS:000709984900009 |
资助机构 | National Key R & D Program of China (Grant No. 2018YFB1304600) ; Natural Science Foundation of China (Grant No. 51775541) ; CAS Interdisciplinary Innovation Team (Grant No. JCTD-2018-11) |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/29800] |
专题 | 中国科学院沈阳自动化研究所 |
通讯作者 | Liu JG(刘金国) |
作者单位 | 1.University of the Chinese Academy of Science, Beijing, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences (CAS), China |
推荐引用方式 GB/T 7714 | Tong YC,Liu JG. Novel power-exponent-type modified RNN for RMP scheme of redundant manipulators with noise and physical constraints[J]. Neurocomputing,2022,467:266-281. |
APA | Tong YC,&Liu JG.(2022).Novel power-exponent-type modified RNN for RMP scheme of redundant manipulators with noise and physical constraints.Neurocomputing,467,266-281. |
MLA | Tong YC,et al."Novel power-exponent-type modified RNN for RMP scheme of redundant manipulators with noise and physical constraints".Neurocomputing 467(2022):266-281. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论