RESEARCH ON HUMAN–ROBOT PHYSICAL INTERACTION CONTROL BASED ON ADAPTIVE IMPEDANCE CONTROL
Qing Sun, Shuai Guo, Leigang Zhang, Sixian Fei
- Year
- 2023
- Citations
- 2
Abstract
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.
Keywords
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