Adaptive Human-Robot Interaction Torque Estimation With High Accuracy and Strong Tracking Ability for a Lower Limb Rehabilitation Robot
文献类型：期刊论文
| 作者 | Liang, Xu1 ; Yan, Yuchen2; Wang, Weiqun3; Su, Tingting4; He, Guangping2; Li, Guotao3; Hou, Zeng-Guang5,6,7
|
| 刊名 | IEEE-ASME TRANSACTIONS ON MECHATRONICS
 |
| 出版日期 | 2024-06-14 |
| 页码 | 12 |
| 关键词 | Adaptive learning human-robot interaction rehabilitation robot torque estimation |
| ISSN号 | 1083-4435 |
| DOI | 10.1109/TMECH.2024.3394491 |
| 通讯作者 | Wang, Weiqun(weiqun.wang@ia.ac.cn) ; Hou, Zeng-Guang(zengguang.hou@ia.ac.cn) |
| 英文摘要 | Accurate acquisition of interactive information is crucial for the effective execution of rehabilitation training. However, due to model and sensor errors, it is difficult to obtain interactive information accurately and quickly. To overcome these challenges, a novel accurate and fast estimation method for the human-robot interaction torques (HRITs) is proposed in this article. First, the HRIT model with order adaptive adjustment ability (HMOAA) is constructed. The polynomial order of HMOAA can be adaptively adjusted based on the partial state estimation, which is more consistent with the dynamic time-varying characteristics of HRIT. Second, the Sage-Husa adaptive strong tracking Kalman filter (SHASTKF) is designed based on the modified Sage-Husa adaptive Kalman filter (SHAKF) and strong tracking Kalman filter (STKF). The SHASTKF can quickly track the abrupt HRIT changes when the subject suddenly exerts active torques in rehabilitation training. Moreover, it also has the ability to recursively estimate the noise characteristics, and can stably complete the HRIT estimation task when the noise characteristics are unknown. Finally, simulations and experiments are conducted to validate the proposed method, and the comparison results demonstrate that the proposed method has good torque estimation precision and fast tracking ability of abrupt changes in HRITs. |
| WOS关键词 | SYSTEMS |
| 资助项目 | National Key R&D Program of China |
| WOS研究方向 | Automation & Control Systems ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001248180700001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key R&D Program of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58758]  |
| 专题 | 多模态人工智能系统全国重点实验室_医疗机器人 |
| 通讯作者 | Wang, Weiqun; Hou, Zeng-Guang |
| 作者单位 | 1.Beijing Jiaotong Univ, Sch Automat & Intelligence, Beijing 100044, Peoples R China 2.North China Univ Technol, Dept Mech & Elect Engn, Beijing 100144, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 4.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China 5.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 7.Macau Univ Sci & Technol, Inst Syst Engn, CASIA MUST Joint Lab Intelligence Sci & Technol, Macau, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liang, Xu,Yan, Yuchen,Wang, Weiqun,et al. Adaptive Human-Robot Interaction Torque Estimation With High Accuracy and Strong Tracking Ability for a Lower Limb Rehabilitation Robot[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2024:12. |
| APA | Liang, Xu.,Yan, Yuchen.,Wang, Weiqun.,Su, Tingting.,He, Guangping.,...&Hou, Zeng-Guang.(2024).Adaptive Human-Robot Interaction Torque Estimation With High Accuracy and Strong Tracking Ability for a Lower Limb Rehabilitation Robot.IEEE-ASME TRANSACTIONS ON MECHATRONICS,12. |
| MLA | Liang, Xu,et al."Adaptive Human-Robot Interaction Torque Estimation With High Accuracy and Strong Tracking Ability for a Lower Limb Rehabilitation Robot".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2024):12. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
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。