CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Adaptive Estimation of Human-Robot Interaction Force for Lower Limb Rehabilitation
Liang, Xu1,2; Wang, Weiqun1; Hou, Zengguang1,2,3; Ren, Shixin1,2; Wang, Jiaxing1,2; Shi, Weiguo1,2; Su, Tingting4
2019
Conference NameInternational Conference on Neural Information Processing
Conference Date2019.12
Conference Place澳大利亚悉尼
Abstract

Human-robot interaction force information is of great significance for realizing safe, compliant and efficient rehabilitation training.
In order to accurately estimate the interaction force during human-robot
interaction, an adaptive method for estimation of human-robot interaction force is proposed in this paper. Firstly, the dynamics of humanrobot system are modeled, which allows to establish a state space equation. Then, the interaction force is described by a polynomial function
of time, and is introduced into the state space equation as a system
state. Meanwhile, the Kalman filter is adopted to estimate the extended
state of system online. Moreover, in order to deal with the uncertainty
of system noise covariance matrix, sage-husa adaptive Kalman filter is
used to correct the covariance matrices of system noises online. Finally,
experiments were carried out on a lower limb rehabilitation robot, and
the results show that the proposed method can precisely estimate the
interaction force and also has good real-time performance.
 

Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/39703
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.CAS Center for Excellence in Brain Science and Intelligence Technology
4.North China University of Technology
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liang, Xu,Wang, Weiqun,Hou, Zengguang,et al. Adaptive Estimation of Human-Robot Interaction Force for Lower Limb Rehabilitation[C],2019.
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