RESEARCH ON HUMAN-ROBOT PHYSICAL INTERACTION CONTROL BASED ON ADAPTIVE IMPEDANCE CONTROL

被引:0
|
作者
Sun, Qing [1 ]
Guo, Shuai [1 ]
Zhang, Leigang [1 ]
Fei, Sixian [1 ]
机构
[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200444, Peoples R China
基金
中国国家自然科学基金;
关键词
Human-robot interaction; dexterity; adaptive; impedance control; local virtual force field; NULL-SPACE COMPLIANCE; REDUNDANT ROBOT; MIRROR THERAPY; STROKE;
D O I
10.1142/S0219519423500525
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
An adaptive impedance control method based on dexterity for compliant interaction is proposed for the problem of compliance and motion performance of the human's healthy side interacting with the manipulator in bilateral mirror rehabilitation motion-assisted training, and constructs a local virtual force field to hinder the movement of the manipulator to the low motion performance region, thus improving the motion performance of the manipulator. Firstly, the dynamic model of the manipulator and the human-robot interaction model based on impedance control are established. Then, a dexterity index based on the condition number is established, and an adaptive impedance control method based on the dexterity is proposed to construct a local virtual force field to hinder the movement of the manipulator to the low motion performance region. Finally, the effectiveness of the proposed method is demonstrated by experiments. The results have shown that the adaptive impedance control method based on dexterity can construct a local virtual force field, which can constrain the motion of the manipulator and keep the robot with good motion performance. It also laid the foundation for the training strategy of bilateral mirror rehabilitation.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] Model reference adaptive impedance control for physical human-robot interaction
    Alqaudi B.
    Modares H.
    Ranatunga I.
    Tousif S.M.
    Lewis F.L.
    Popa D.O.
    [J]. Alqaudi, Bakur (balqaudi@yic.edu.sa), 1600, South China University of Technology (14): : 68 - 82
  • [2] Physical human-robot interaction force control method based on adaptive variable impedance
    Dong, Jianwei
    Xu, Jianming
    Zhou, Qiaoqian
    Hu, Songda
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2020, 357 (12): : 7864 - 7878
  • [3] Adaptive Impedance Decentralized Control of Modular Robot Manipulators for Physical Human-robot Interaction
    Bo Dong
    Yusheng Jing
    Xinye Zhu
    Yiming Cui
    Tianjiao An
    [J]. Journal of Intelligent & Robotic Systems, 2023, 109
  • [4] Adaptive Impedance Decentralized Control of Modular Robot Manipulators for Physical Human-robot Interaction
    Dong, Bo
    Jing, Yusheng
    Zhu, Xinye
    Cui, Yiming
    An, Tianjiao
    [J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2023, 109 (03)
  • [5] Impedance Learning-Based Adaptive Control for Human-Robot Interaction
    Sharifi, Mojtaba
    Azimi, Vahid
    Mushahwar, Vivian K.
    Tavakoli, Mahdi
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2022, 30 (04) : 1345 - 1358
  • [6] Sparse Bayesian Learning-Based Adaptive Impedance Control in Physical Human-Robot Interaction
    Li, Kelin
    Zhao, Huan
    Nuchkrua, Thanana
    Yuan, Ye
    Ding, Han
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO), 2018, : 2379 - 2385
  • [7] Impedance Control for Human-Robot Interaction with an Adaptive Fuzzy Approach
    Li, Ping
    Ge, Shuzhi Sam
    Wang, Chen
    [J]. 2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 5889 - 5894
  • [8] Model reference adaptive impedance control in Cartesian coordinates for physical human-robot interaction
    Sharifi, Mojtaba
    Behzadipour, Saeed
    Vossoughi, G. R.
    [J]. ADVANCED ROBOTICS, 2014, 28 (19) : 1277 - 1290
  • [9] Mimetic Communication with Impedance Control for Physical Human-Robot Interaction
    Lee, Dongheui
    Ott, Christian
    Nakamura, Yoshihiko
    [J]. ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7, 2009, : 4281 - +
  • [10] Impedance learning control for physical human-robot cooperative interaction
    Brahmi, Brahim
    El Bojairami, Ibrahim
    Laraki, Mohamed-Hamza
    El-Bayeh, Claude Ziad
    Saad, Maarouf
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 2021, 190 : 1224 - 1242