康复辅助机器人及其物理人机交互方法

彭亮; 侯增广; 王晨; 罗林聪; 王卫群

doi:10.16383/j.aas.2018.c180209

康复辅助机器人及其物理人机交互方法

doi: 10.16383/j.aas.2018.c180209

彭亮^1,,
侯增广^1,2,3, ,,
王晨^1,2,,
罗林聪^1,2,,
王卫群^1,

1.
中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京 100190
2.
中国科学院大学北京 100049
3.
中国科学院脑科学与智能技术卓越创新中心北京 100190

基金项目:

北京市自然科学基金 L172050

国家自然科学基金 61533016

国家自然科学基金 61603386

北京市自然科学基金 Z170003

国家自然科学基金 U1613228

中国科学院战略性先导科技专项 XDBS01040100

国家自然科学基金 61720106012

详细信息

作者简介:
彭亮  中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员.主要研究方向为康复机器人, 生物信号处理.E-mail:liang.peng@ia.ac.cn

王晨  中国科学院自动化研究所复杂系统管理与控制国家重点实验室控制科学与工程专业博士研究生.主要研究方向为康复机器人控制.E-mail:wangchen2016@ia.ac.cn

罗林聪  中国科学院自动化研究所复杂系统管理与控制国家重点实验室控制科学与工程专业博士研究生.主要研究方向为康复机器人控制.E-mail:luolincong2014@ia.ac.cn

王卫群  中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员.主要研究领域为康复机器人, 人机动力学, 人-机交互控制, 生物电信号处理. E-mail:weiqun.wang@ia.ac.cn

通讯作者:
侯增广中国科学院自动化研究所研究员, 复杂系统管理与控制国家重点实验室副主任.主要研究方向为机器人控制, 智能控制理论与方法, 嵌入式系统软硬件开发, 医学和健康自动化领域的康复与手术机器人.本文通信作者.E-mail:zengguang.hou@ia.ac.cn

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出版历程
- 收稿日期: 2018-04-11
- 录用日期: 2018-08-01
- 刊出日期: 2018-11-20

Physical Interaction Methods for Rehabilitation and Assistive Robots

PENG Liang^1
,,
HOU Zeng-Guang^{1,2,3
, ,},
WANG Chen^{1,2
,},
LUO Lin-Cong^{1,2
,},
WANG Wei-Qun^1
,

1.
State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences(CAS), Beijing 100190
2.
University of Chinese Academy of Sciences, Beijing 100049
3.
CAS Center for Excellence in Brain Science and Intelligence Technology, Beijing 100190

Funds:

Beijing Natural Science Foundation L172050

National Natural Science Foundation of China 61533016

National Natural Science Foundation of China 61603386

Beijing Natural Science Foundation Z170003

National Natural Science Foundation of China U1613228

Chinese Academy of Sciences Strategic Pilot Project XDBS01040100

National Natural Science Foundation of China 61720106012

More Information

Author Bio:
Assistant professor at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. His research interest covers rehabilitation robots and biomedical signal processing

Ph. D. candidate in control science and engineering at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. Her research interest covers the control of rehabilitation robots

Ph. D. candidate in control science and engineering at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. His research interest covers the control of rehabilitation robots

Associate professor at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China. His research interest covers rehabilitation robot, dynamics of human-robot system, humanrobot interaction control, and biomedical signal processing

Corresponding author: HOU Zeng-Guang Professor and deputy director at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. His research interest covers robotics and intelligent control with applications to rehabilitation and surgical robots for medical and health automation. Corresponding author of this paper

摘要

摘要: 面对中国社会快速老龄化现状和庞大的残疾人群，康复辅助机器人研究具有重要学术价值和广阔的应用前景.康复辅助机器人研究涉及神经科学、生物力学、机器人自动控制等领域知识，是机器人最具挑战性和最受关注的研究领域之一.与其他机器人不同，康复辅助机器人的作用对象是人，存在人与机器人的信息交流和能量交换，物理人机交互控制方法是其研究核心和关键技术.本文以神经康复机器人、穿戴式外骨骼、智能假肢等应用为例，介绍当前的研究现状，并重点介绍人体运动意图识别方法和交互控制方法等研究重点和难点.最后展望该领域的未来技术发展方向.
- 康复机器人 /
- 辅助机器人 /
- 物理人机交互 /
- 意图识别 /
- 交互控制
Abstract: With the rapid growth of China's aging and disabled population, researches on rehabilitation and assistive robots have great value to technical study and good prospects for applications. Rehabilitation and assistive robots involve the domain knowledge of neuroscience, biomechanics, robot automatic control, etc., thus are one of the most challenging and most concerned research areas of robotics. As the application contexts of rehabilitation and assistance entail information communication and energy exchange between man and robot, the physical human-robot interaction control method is the key theme. This article briefly introduces the states of the art of neurorehabilitation robots, wearable exoskeletons, and intelligent prostheses, and focuses on the key issues and research priorities in human motion intent detection methods and interaction control methods. Finally, the future development directions are prospected.
- Rehabilitation robot /
- assistive robot /
- physical human-robot interaction /
- intention detection /
- interaction control
注释:

1) 本文责任编委孙健

HTML全文

图 1 MIT-Manus与Armeo Power上肢康复机器人

Fig. 1 MIT-Manus and Armeo Power upper limb rehabilitation robots

下载: 全尺寸图片幻灯片

图 2 瑞士Hocoma公司的Lokomat下肢康复机器

Fig. 2 Lokomat lower limb rehabilitation robot

下载: 全尺寸图片幻灯片

图 3 外骨骼机器人

Fig. 3 Exoskeletal robots

下载: 全尺寸图片幻灯片

图 4 美国哈佛大学研制的Soft Exosuits外骨骼机器人

Fig. 4 Soft Exosuits from Harvard University

下载: 全尺寸图片幻灯片

图 5 基于TMR手术和表面肌电信号控制的动力型假肢

Fig. 5 Power prothesis controlled by sEMG signal via targeted muscle reinnervation

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图 6 仿生假肢与动力假肢

Fig. 6 Bionic prostheis and powered prosthesis

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