| Data-driven Motion-force Control for Acceleration Minimization of Robots | |
Liu, M(刘梅)1 ; Fu, Dongyang2; Liu, Kun1; Jin, L(金龙)1 | |
| 2023 | |
| Source Publication | 13th International Conference on Information Science and Technology, ICIST 2023 - Proceedings Impact Factor & Quartile Of Published Year The Latest Impact Factor & Quartile |
| Conference Name | 13th International Conference on Information Science and Technology, ICIST 2023 |
| Conference Date | December 8, 2023 - December 14, 2023 |
| Pages | 232-237 |
| Abstract | It is tricky to accurately solve the redundancy solutions of redundant robots with uncertain-structure information. Besides, position-force control as a challenging technical problem is significant for redundant robots with impact forces generated by the end-effector especially. Noteworthily, without considering posture maintenance, the end-effector of redundant robots may experience jittery movements and potentially fail in accurately tracking the target. A data-driven motion-force scheme, considering constraints including position-force control, posture maintaining, and physical joint limits, solved by neural dynamics in the acceleration level, is proposed for redundant robots with unknown structure information. Comparisons and simulation experiments are supplied to substantiate the availability and superiority of the proposed date-driven motion-force scheme. © 2023 IEEE. |
| Keyword | End effectors Position control Redundant manipulators Data driven Data-driven methods Impact force Minimisation Motion-force control Neural dynamics Position/force control Redundant robot Structure information Uncertain structures |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| DOI | 10.1109/ICIST59754.2023.10367171 |
| Indexed By | EI |
| Language | 英语 |
| Funding Organization | Chongqing Three Gorges University; City University of Hong Kong; The British University in Egypt |
| EI Accession Number | 20240415434314 |
| EI Keywords | Force control |
| EI Classification Number | 731.3 Specific Variables Control ; 731.5 Robotics |
| Original Document Type | Conference article (CA) |
| Conference Place | Cairo, Egypt |
| Citation statistics | |
| Document Type | 会议论文 |
| Identifier | https://ir.lzu.edu.cn/handle/262010/583802 |
| Collection | 信息科学与工程学院 |
| Affiliation | 1.School of Information Science and Engineering, Lanzhou University, Lanzhou, China; 2.School of Electronic and Information Engineering, Guangdong Ocean University, Guangdong, China |
| First Author Affilication | School of Information Science and Engineering |
| First Signature Affilication | School of Information Science and Engineering |
| Recommended Citation GB/T 7714 | Liu, Mei,Fu, Dongyang,Liu, Kun,et al. Data-driven Motion-force Control for Acceleration Minimization of Robots[C],2023:232-237. |
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