一种基于非线性振荡器的步态轨迹自适应算法

罗林聪; 侯增广; 王卫群; 彭亮

doi:10.16383/j.aas.2016.c160205

一种基于非线性振荡器的步态轨迹自适应算法

doi: 10.16383/j.aas.2016.c160205

罗林聪^1,2,,
侯增广^1,3, ,,
王卫群^1,,
彭亮^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:

北京市科技计划 Z161100001516004

国家自然科学基金 61421004

中国科学院先导科技专项 XDB02080000

国家自然科学基金 61225017

国家自然科学基金 61533016

详细信息

作者简介:
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

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.主要研究方向为机器人控制, 生物信号处理.E-mail:liang.peng@ia.ac.cn

通讯作者:
侯增广中国科学院自动化研究所研究员.主要研究方向为机器人控制, 智能控制理论与方法, 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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- 被引次数: 14
出版历程
- 收稿日期: 2016-03-02
- 录用日期: 2016-10-14
- 刊出日期: 2016-12-01

A Gait Trajectory Adaptation Algorithm Based on Nonlinear Oscillator

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

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

Funds:

Beijing Science and Technology Project Z161100001516004

National Natural Science Foundation of China 61421004

Strategic Priority Research Program of the Chinese Academy of Sciences XDB02080000

National Natural Science Foundation of China 61225017

National Natural Science Foundation of China 61533016

More Information

Author Bio:
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 main research interest is rehabilitation robot control

Associate 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 robot, dynamics of human-robot system, human-robot interaction control, and biomedical signal processing

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 robotics and biomedical signal processing

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

摘要

摘要: 步态训练轨迹是影响康复训练效果的一项重要因素，而自适应性对于下肢康复机器人的临床应用具有重要的意义.振荡器可通过在线调节参数而输出不同波形的周期信号，常用于康复机器人步态轨迹的生成.本文在高斯核函数非线性振荡器的基础上提出了一种下肢康复机器人步态轨迹自适应算法.该算法通过轨迹偏差实现对参考轨迹波形的调节，并且用相位偏差曲线面积实现参考轨迹周期的自适应.本文首先介绍了用于生成步态参考轨迹的非线性振荡器的数学模型；其次，详细描述了基于该模型的参考轨迹波形和周期自适应算法；最后，以悬挂减重式下肢康复机器人为研究对象，建立机器人与人体下肢仿真模型，对所提出的步态参考轨迹自适应算法进行仿真实验，并验证了该算法的可行性.
- 下肢康复机器人 /
- 步态轨迹 /
- 振荡器 /
- 自适应算法 /
- 步态训练
Abstract: Gait trajectory is an important factor to the effects of rehabilitation with adaptability has great significance for clinical application of lower limb rehabilitation robot. The oscillator can output various waveforms and periodic smooth signals by adjusting parameters online, which is frequently used to generate gait reference trajectory for rehabilitation robots. This paper proposes a gait trajectory adaptation algorithm for lower limb rehabilitation robot based on Gaussian kernel nonlinear oscillators. In the algorithm, trajectory deviation is used to adjust the waveform of reference trajectory, and the area of phase deviation curve is used to adjust the period of reference trajectory. Firstly, the paper introduces the nonlinear oscillator model for generating gait reference trajectory. Then, the adaptation algorithms for gait trajectory waveform and period are described based on this mathematical model. Finally, a human-robot simulation model is built based on a weight supporting rehabilitation robot system. These algorithms are validated by simulation experiments and the results demonstrate the feasibility of proposed algorithms.
- Lower limb rehabilitation robot /
- gait trajectory /
- oscillators /
- adaptive algorithm /
- gait training
注释:

1) 本文责任编委王启宁

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本文责任编委王启宁

图 1 Lokomat康复机器人^[18]

Fig. 1 Lokomat rehabilitation robot^[18]

下载: 全尺寸图片幻灯片

图 2 相位偏差

Fig. 2 Phase deviation

下载: 全尺寸图片幻灯片

图 3 系统结构图

Fig. 3 System block diagram

下载: 全尺寸图片幻灯片

图 4 条件1)下的波形自适应结果

Fig. 4 The waveform adaptation results on condition 1)

下载: 全尺寸图片幻灯片

图 5 条件2)下的周期自适应结果

Fig. 5 The period adaptation results on condition 2)

下载: 全尺寸图片幻灯片

图 6 条件3)下的步态轨迹自适应结果

Fig. 6 The gait trajectory adaptation results on condition 3)

下载: 全尺寸图片幻灯片

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