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CLC number: TP242

On-line Access: 2018-11-11

Received: 2016-10-26

Revision Accepted: 2017-04-26

Crosschecked: 2018-09-09

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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.9 P.1076-1085


Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification

Author(s):  Yi Long, Zhi-jiang Du, Wei-dong Wang, Long He, Xi-wang Mao, Wei Dong

Affiliation(s):  State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China; more

Corresponding email(s):   dongwei@hit.edu.cn

Key Words:  Exoskeleton, Physical human-robot interaction, Torque sensor, Human gait, Kalman smoother

Yi Long, Zhi-jiang Du, Wei-dong Wang, Long He, Xi-wang Mao, Wei Dong. Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(9): 1076-1085.

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journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

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%T Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification
%A Yi Long
%A Zhi-jiang Du
%A Wei-dong Wang
%A Long He
%A Xi-wang Mao
%A Wei Dong
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601667

T1 - Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification
A1 - Yi Long
A1 - Zhi-jiang Du
A1 - Wei-dong Wang
A1 - Long He
A1 - Xi-wang Mao
A1 - Wei Dong
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 9
SP - 1076
EP - 1085
%@ 2095-9184
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1601667

We proposed a lower extremity exoskeleton for power amplification that perceives intended human motion via human-exoskeleton interaction signals measured by biomedical or mechanical sensors, and estimates human gait trajectories to implement corresponding actions quickly and accurately. In this study, torque sensors mounted on the exoskeleton links are proposed for obtaining physical human-robot interaction (pHRI) torque information directly. A kalman smoother is adopted for eliminating noise and smoothing the signal data. Simultaneously, the mapping from the pHRI torque to the human gait trajectory is defined. The mapping is derived from the real-time state of the robotic exoskeleton during movement. The walking phase is identified by the threshold approach using ground reaction force. Based on phase identification, the human gait can be estimated by applying the proposed algorithm, and then the gait is regarded as the reference input for the controller. A proportional-integral-derivative control strategy is constructed to drive the robotic exoskeleton to follow the human gait trajectory. Experiments were performed on a human subject who walked on the floor at a natural speed wearing the robotic exoskeleton. Experimental results show the effectiveness of the proposed strategy.


摘要:提出一种能通过生物医学或机械传感器测量人机交互信号感知人体运动的用于助力的下肢外骨骼,并估计人体步态轨迹以快速准确地实施相应动作。提出安装在外骨骼上的力矩传感器直接获得物理人机交互(physical human-robot inter action,pHRI)力矩信息。采用卡尔曼平滑器消除噪声并平滑信号,定义了从pHRI力矩到人体步态轨迹的映射关系。通过外骨骼在运动期间的实时状态推导该映射,并通过基于地面反作用力的阈值方法识别人体运动相位。基于相位识别,通过所提算法估计人体步态,将步态辨识结果作为控制器的参考输入。用一种常规比例-积分-微分(proportional-integral-derivative,PID)控制策略控制外骨骼跟随人体步态运动。测试人员穿戴外骨骼以自然速度在水平面进行行走实验,实验结果验证了所提策略的有效性。


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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