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A controller for walking derived from how humans recover from perturbations.

Varun Joshi1, Manoj Srinivasan1

  • 1Mechanical and Aerospace Engineering, The Ohio State University, Columbus, OH 43210, USA.

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|August 15, 2019
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Researchers developed a human-like walking controller for a bipedal model by analyzing treadmill data. This controller enables robust recovery from significant external perturbations, enhancing robotic stability.

Keywords:
feedback controlhybrid systemslocomotionroboticssystem identificationwalking

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Area of Science:

  • Robotics
  • Biomechanics
  • Control Theory

Background:

  • Human walking stability relies on complex control mechanisms not fully understood.
  • Existing walking simulations and robots lack controllers derived from human data.

Purpose of the Study:

  • To derive a feedback controller for a walking model based on human walking data.
  • To enable a bipedal model to mimic human stability and recovery responses to perturbations.

Main Methods:

  • Subjects walked on a treadmill while subjected to thousands of unforeseen perturbations.
  • Data on human recovery responses were collected and analyzed.
  • A linear controller was derived for an inverted pendulum walking model using this data.

Main Results:

  • The derived controller enables a bipedal model to recover from perturbations like humans.
  • The model demonstrated recovery from perturbations over twenty times larger than normal walking deviations.
  • The biped's stability proved robust to significant changes in body and feedback parameters.

Conclusions:

  • A human-inspired feedback controller for bipedal walking was successfully derived.
  • This controller significantly enhances robotic stability and perturbation recovery.
  • The findings offer a pathway for developing more human-like robotic locomotion.