2.765

2022影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

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

罗林聪, 侯增广, 王卫群, 彭亮. 一种基于非线性振荡器的步态轨迹自适应算法. 自动化学报, 2016, 42(12): 1951-1959. doi: 10.16383/j.aas.2016.c160205
引用本文: 罗林聪, 侯增广, 王卫群, 彭亮. 一种基于非线性振荡器的步态轨迹自适应算法. 自动化学报, 2016, 42(12): 1951-1959. doi: 10.16383/j.aas.2016.c160205
LUO Lin-Cong, HOU Zeng-Guang, WANG Wei-Qun, PENG Liang. A Gait Trajectory Adaptation Algorithm Based on Nonlinear Oscillator. ACTA AUTOMATICA SINICA, 2016, 42(12): 1951-1959. doi: 10.16383/j.aas.2016.c160205
Citation: LUO Lin-Cong, HOU Zeng-Guang, WANG Wei-Qun, PENG Liang. A Gait Trajectory Adaptation Algorithm Based on Nonlinear Oscillator. ACTA AUTOMATICA SINICA, 2016, 42(12): 1951-1959. 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
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

A Gait Trajectory Adaptation Algorithm Based on Nonlinear Oscillator

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: 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.
    1)  本文责任编委 王启宁
  • 图  1  Lokomat康复机器人[18]

    Fig.  1  Lokomat rehabilitation robot[18]

    图  2  相位偏差

    Fig.  2  Phase deviation

    图  3  系统结构图

    Fig.  3  System block diagram

    图  4  条件1)下的波形自适应结果

    Fig.  4  The waveform adaptation results on condition 1)

    图  5  条件2)下的周期自适应结果

    Fig.  5  The period adaptation results on condition 2)

    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)

  • [1] Bourbonnais D, Noven S V. Weakness in patients with hemiparesis. American Journal of Occupational Therapy, 1989, 43(5):313-319 doi: 10.5014/ajot.43.5.313
    [2] Barbeau H, Ladouceur M, Norman K E, Pépin A, Leroux A. Weakness in patients with hemiparesis:evaluation, treatment, and functional recovery. Archives of Physical Medicine and Rehabilitation, 1999, 80(2):225-235 doi: 10.1016/S0003-9993(99)90126-0
    [3] Teasell R W, Kalra L. What's new in stroke rehabilitation. Stroke, 2004, 35(2):383-385 doi: 10.1161/01.STR.0000115937.94104.76
    [4] Dobkin B H. Strategies for stroke rehabilitation. The Lancet Neurology, 2004, 3(9):528-536 doi: 10.1016/S1474-4422(04)00851-8
    [5] Huo W G, Mohammed S, Moreno J C, Amirat Y. Lower limb wearable robots for assistance and rehabilitation:a state of the art. IEEE Systems Journal, 2016, 10(3):1068-1081 doi: 10.1109/JSYST.2014.2351491
    [6] Marchal-Crespo L, Reinkensmeyer D J. Review of control strategies for robotic movement training after neurologic injury. Journal of Neuroengineering and Rehabilitation, 2009, 6(1):Article No.20 doi: 10.1186/1743-0003-6-20
    [7] Chen G, Chan C K, Guo Z, Yu H Y. A review of lower extremity assistive robotic exoskeletons in rehabilitation therapy. Critical Reviews in Biomedical Engineering, 2013, 41(4-5):343-363 doi: 10.1615/CritRevBiomedEng.v41.i4-5
    [8] Veneman J F, Kruidhof R, Hekman E E G, Ekkelenkamp R, Van Asseldonk E H F, van der Kooij H. Design and evaluation of the LOPES exoskeleton robot for interactive gait rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2007, 15(3):379-386 doi: 10.1109/TNSRE.2007.903919
    [9] Jezernik S, Colombo G, Morari M. Automatic gait-pattern adaptation algorithms for rehabilitation with a 4-DOF robotic orthosis. IEEE Transactions on Robotics and Automation, 2004, 20(3):574-582 doi: 10.1109/TRA.2004.825515
    [10] Banala S K, Kim S H, Agrawal S K, Scholz J P. Robot assisted gait training with active leg exoskeleton (ALEX). IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2009, 17(1):2-8 doi: 10.1109/TNSRE.2008.2008280
    [11] Zanotto D, Stegall P, Agrawal S K. Adaptive assist-as-needed controller to improve gait symmetry in robot-assisted gait training. In:Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA). Hong Kong, China:IEEE, 2014. 724-729
    [12] Aoyagi D, Ichinose W E, Harkema, S J, Reinkensmeyer D J, Bobrow J E. A robot and control algorithm that can synchronously assist in naturalistic motion during body-weight-supported gait training following neurologic injury. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2007, 15(3):387-400 doi: 10.1109/TNSRE.2007.903922
    [13] Hesse S, Uhlenbrock D. A mechanized gait trainer for restoration of gait. Journal of Rehabilitation Research and Development, 2000, 37(6):701-708 http://www.rehab.research.va.gov/jour/00/37/6/pdf/hesse.pdf
    [14] Schmidt H, Werner C, Bernhardt R, Hesse S, Krüger J. Gait rehabilitation machines based on programmable footplates. Journal of Neuroengineering and Rehabilitation, 2007, 4(1):218-227 https://www.researchgate.net/publication/6514377_Gait_rehabilitation_machines_based_on_programmable_footplates
    [15] Banala S K, Agrawal S K, Scholz J P. Active leg exoskeleton (ALEX) for gait rehabilitation of motor-impaired patients. In:Proceedings of the 10th International Conference on Rehabilitation Robotics. Noordwijk, Netherlands:IEEE, 2007. 401-407
    [16] Wheeler J W, Krebs H I, Hogan N. An ankle robot for a modular gait rehabilitation system. In:Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems. Sendai, Japan:IEEE, 2004. 1680-1684
    [17] Emken J L, Harkema S J, Beres-Jones J A, Ferreira C K, Reinkensmeyer D J. Feasibility of manual teach-and-replay and continuous impedance shaping for robotic locomotor training following spinal cord injury. IEEE Transactions on Biomedical Engineering, 2008, 55(1):322-334 doi: 10.1109/TBME.2007.910683
    [18] Hocoma. Lokomat[Online], available:https://www.hocoma.com/world/en/media-center/media-images/loko-mat/, June 27, 2016
    [19] Vallery H, van Asseldonk E H F, Buss M, van der Kooij H. Reference trajectory generation for rehabilitation robots:complementary limb motion estimation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2009, 17(1):23-30 doi: 10.1109/TNSRE.2008.2008278
    [20] Riener R, Lünenburger L, Jezernik S, Anderschitz M, Colombo G, Dietz V. Patient-cooperative strategies for robot-aided treadmill training:first experimental results. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2005, 13(3):380-394 doi: 10.1109/TNSRE.2005.848628
    [21] Ijspeert A J. Central pattern generators for locomotion control in animals and robots:a review. Neural Networks, 2008, 21(4):642-653 doi: 10.1016/j.neunet.2008.03.014
    [22] Seo K, Hyung S, Choi B K, Lee Y, Shim Y. A new adaptive frequency oscillator for gait assistance. In:Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA). Seattle, Washington, USA:IEEE, 2015. 5565-5571
    [23] Ronsse R, Vitiello N, Lenzi T, van den Kieboom J, Carrozza M C, Ijspeert A J. Human-robot synchrony:flexible assistance using adaptive oscillators. IEEE Transactions on Biomedical Engineering, 2011, 58(4):1001-1012 doi: 10.1109/TBME.2010.2089629
    [24] Gams A, Ijspeert A J, Schaal S, Lenaréciéc J. On-line learning and modulation of periodic movements with nonlinear dynamical systems. Autonomous Robots, 2009, 27(1):3-23 doi: 10.1007/s10514-009-9118-y
    [25] Righetti L, Buchli J, Ijspeert A J. Dynamic Hebbian learning in adaptive frequency oscillators. Physica D:Nonlinear Phenomena, 2006, 216(2):269-281 doi: 10.1016/j.physd.2006.02.009
    [26] Karnjanaparichat T, Pongvuthithum R. Synchronization control scheme for gait training robot and treadmill. In:Proceedings of the 2014 International Computer Science and Engineering Conference (ICSEC). Khon Kaen, Thailand:IEEE, 2014. 481-485
    [27] Petriéc T, Gams A, Ijspeert A J, éZlajpah L. On-line frequency adaptation and movement imitation for rhythmic robotic tasks. The International Journal of Robotics Research, 2011, 30(14):1775-1788 doi: 10.1177/0278364911421511
    [28] Hogan N. Impedance control:an approach to manipulation:Part Ⅱ-implementation. Journal of Dynamic Systems, Measurement, and Control, 1985, 107(1):8-16 doi: 10.1115/1.3140713
  • 加载中
图(6)
计量
  • 文章访问数:  2246
  • HTML全文浏览量:  379
  • PDF下载量:  1046
  • 被引次数: 0
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

目录

    /

    返回文章
    返回