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Variable Impedance Control Based on Target Position and Tracking Error for Rehabilitation Robots During a Reaching

Rongrong Tang1,2, Qianqian Yang1,2,3, Rong Song1,2

  • 1The Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China.

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Summary

This study introduces a variable impedance control (vIC) algorithm for human-robot interaction. The new vIC method enhances robot performance by improving tracking accuracy and smoothness while reducing interaction forces.

Keywords:
reaching taskrehabilitation robotsmooth trajectorytarget positiontracking errorvariable impedance

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Area of Science:

  • Robotics
  • Human-Robot Interaction
  • Control Systems

Background:

  • Achieving human-like robot performance in physical interactions is crucial for applications like rehabilitation.
  • Existing impedance control methods often lack adaptability to dynamic interaction conditions.

Purpose of the Study:

  • To propose a novel variable impedance control (vIC) algorithm that mimics human-like characteristics for physical human-robot interaction.
  • To enhance robot performance during reaching tasks by adapting control parameters.

Main Methods:

  • Developed a vIC algorithm where damping varies with target position and tracking error.
  • Compared the proposed vIC against constant-parameter impedance control (IC) and a tracking-error-based vIC (vIC-e).
  • Validated algorithms through simulations and experimental implementation on a cable-driven rehabilitation robot.

Main Results:

  • The proposed vIC demonstrated improved tracking accuracy compared to IC and vIC-e.
  • Trajectory smoothness was enhanced with the proposed vIC algorithm.
  • A significant reduction in interaction forces was observed using the proposed vIC.

Conclusions:

  • The proposed vIC algorithm successfully achieves anthropomorphic performance in human-robot interaction.
  • Variable impedance control, adapting to both target position and tracking error, offers superior performance in rehabilitation robotics.
  • This approach enhances safety and effectiveness in physical human-robot collaboration.