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Human-Inspired Eigenmovement Concept Provides Coupling-Free Sensorimotor Control in Humanoid Robot.

Alexei V Alexandrov1, Vittorio Lippi2, Thomas Mergner2

  • 1Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of ScienceMoscow, Russia.

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|May 11, 2017
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Summary

Eigenmovement (EM) control offers a stable, coupling-free alternative for humanoid robot balance. Tests confirm its robustness against sensor noise, delays, and mechanical issues, validating its potential for human-like control.

Keywords:
bioroboticseigenmovementshuman sensorimotor systemmotor controlneuromechanics

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Area of Science:

  • Robotics
  • Biomechanics
  • Control Theory

Background:

  • Controlling multi-body systems like robots and humans often struggles with destabilizing dynamic coupling effects between linked segments.
  • Current robotic solutions rely on complex full state feedback controllers.
  • Eigenmovement (EM) control presents a theoretically stable and parsimonious alternative for human hip-ankle coordination.

Purpose of the Study:

  • To investigate the real-world robustness of the Eigenmovement (EM) control strategy.
  • To assess EM control's performance against sensor noise, mechanical non-linearities (dead zones), and human-like feedback time delays.
  • To evaluate EM control for hip-ankle movements in a balancing humanoid robot.

Main Methods:

  • Introduction of the Eigenmovement (EM) concept and controller.
  • Identification of robot dynamics using a biomechanical approach.
  • Conducting robot tests in a human posture control laboratory setting.

Main Results:

  • The EM controller demonstrated stable control for proactive movements and reactive balancing during support surface disturbances (tilts and translations).
  • The controller showed robustness against simulated real-world challenges like noisy sensors and time delays.
  • Preliminary robot-human comparisons revealed both similarities and differences in control strategies.

Conclusions:

  • The Eigenmovement concept is a viable candidate for modeling human sensorimotor control.
  • Human-inspired robot experiments can aid in selecting control strategies and improving humanoid robot and rehabilitation device design.