Human-robot coupling dynamic modeling and analysis for upper limb rehabilitation robots
Qiaolian Xie1,2,3, Qiaoling Meng1,2,3, Yue Dai1,2,3
1Rehabilitation Engineering and Technology Institute, University of Shanghai for Science and Technology, Shanghai, China.
Summary
Accurate human-robot coupling (HRC) dynamics modeling improves control for upper limb rehabilitation robots. This study demonstrates HRC torque is more precise than robot torque for enhanced rehabilitation robot performance.
Area of Science:
- Robotics
- Rehabilitation Engineering
- Biomechanics
Background:
- Upper limb rehabilitation robots are crucial for stroke recovery.
- Human-robot coupling (HRC) dynamics significantly impact rehabilitation robot control and human-robot interaction.
Purpose of the Study:
- To develop and analyze HRC dynamics modeling for precise control of upper limb rehabilitation robots.
- To enhance dynamic control accuracy in robotic-assisted rehabilitation.
Main Methods:
- Analyzed force interactions between human arm and robot to derive HRC torque.
- Utilized Lagrangian equations and step-by-step parameter identification for a 2-DOF robot (FLEXO-Arm).
- Calculated HRC torque and robot torque using identified dynamic parameters.
Main Results:
- Parameter identification yielded HRC and robot torques with approximately 10% root mean square (RMS) error.
- HRC torque demonstrated higher accuracy compared to robot torque when validated against sensor measurements.
- The error in robot torque was over twice that of the HRC torque.
Conclusions:
- The developed HRC dynamics modeling enables more accurate dynamic control of upper limb rehabilitation robots.
- This advancement can lead to improved effectiveness in stroke rehabilitation through enhanced robot-human interaction.
