Data-Driven Motion-Force Control Scheme for Redundant Manipulators: A Kinematic Perspective
文献类型：期刊论文
| 作者 | Fan, Jialiang2,3; Jin, Long1,4; Xie, Zhengtai2; Li, Shuai2; Zheng, Yu5 |
| 刊名 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
 |
| 出版日期 | 2022-08-01 |
| 卷号 | 18期号:8页码:5338-5347 |
| 关键词 | Manipulators Kinematics End effectors Force Jacobian matrices Robots Force control Data driven kinematic control motion-force control recurrent neural network (RNN) redundant manipulators |
| ISSN号 | 1551-3203 |
| DOI | 10.1109/TII.2021.3125449 |
| 通讯作者 | Jin, Long(jinlongsysu@foxmail.com) |
| 英文摘要 | Redundant manipulators play a critical role in industry and academia, which can be controlled from the kinematic or dynamic perspective. The motion-force control of redundant manipulators is a core problem in robot control, especially for the task requiring keeping contact with objectives, such as cutting, polishing, deburring, etc. However, when a manipulator's model structure is unknown, it is challenging to take motion-force control of redundant manipulators. This article proposes a data-driven-based motion-force control scheme, which solves the motion-force control problem from the kinematic perspective. The scheme can take effect and estimate the structure information, i.e., the model parameters involved in the forward kinematics when the structure of the manipulator is incomplete or unknown. A recurrent neural network is devised to find the solution to the scheme. Besides, the theoretical analysis is presented to prove the correctness of the scheme. Simulations and physical experiments running on seven degrees of freedom redundant manipulators illustrate the superb performance and practicability of the scheme intuitively. The key contribution of this article is that, for the first time, a motion-force control scheme aided with data-driven technology is proposed from a kinematic perspective for the redundant manipulators. |
| 资助项目 | National Natural Science Foundation of China[62176109] ; CIE-Tencent Robotics X Rhino-Bird Focused Research Program[2021-01] ; Natural Science Foundation of Chongqing, China[cstc2020jcyjzdxmX0028] ; Chinese Academy of Sciences Light of West China Program ; Natural Science Foundation of Gansu Province[21JR7RA531] ; Natural Science Foundation of Gansu Province[20JR10RA639] ; CAAI-Huawei MindSpore Open Fund, China[CAAIXSJLJJ-2020-012 A] ; Gansu Provincial Youth Doctoral Fund of Colleges and Universities[2021QB-003] ; Fundamental Research Funds for the Central Universities[lzujbky-2021-65] ; Education Department of Gansu Province: Excellent Graduate student Innovation Star project[2021CXZX-120] ; Supercomputing Center of Lanzhou University |
| WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000793847600034 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/15897]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Jin, Long |
| 作者单位 | 1.Lanzhou Univ, Dept Comp Sci, Lanzhou 730000, Peoples R China 2.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China 3.Acad Plateau Sci & Sustainabil, Xining 810016, Peoples R China 4.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China 5.Robot X, Tencent, Shenzhen 518057, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fan, Jialiang,Jin, Long,Xie, Zhengtai,et al. Data-Driven Motion-Force Control Scheme for Redundant Manipulators: A Kinematic Perspective[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2022,18(8):5338-5347. |
| APA | Fan, Jialiang,Jin, Long,Xie, Zhengtai,Li, Shuai,&Zheng, Yu.(2022).Data-Driven Motion-Force Control Scheme for Redundant Manipulators: A Kinematic Perspective.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,18(8),5338-5347. |
| MLA | Fan, Jialiang,et al."Data-Driven Motion-Force Control Scheme for Redundant Manipulators: A Kinematic Perspective".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 18.8(2022):5338-5347. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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