A controller for walking derived from how humans recover from perturbations

Humans can walk without falling despite some external perturbations, but the control mechanisms by which this stability is achieved have not been fully characterized. While numerous walking simulations and robots have been constructed, no full-state walking controller for even a simple model of walking has been derived from human walking data. Here, to construct such a feedback controller, we applied thousands of unforeseen perturbations to subjects walking on a treadmill and collected data describing their recovery to normal walking. Using these data, we derived a linear controller to make the classical inverted pendulum model of walking respond to perturbations like a human. The walking model consists of a point-mass with two massless legs and can be controlled only through the appropriate placement of the foot and the push-off impulse applied along the trailing leg. We derived how this foot placement and push-off impulse are modulated in response to upper-body perturbations in various directions. This feedback-controlled biped recovers from perturbations in a manner qualitatively similar to human recovery. The biped can recover from perturbations over twenty times larger than deviations experienced during normal walking and the biped’s stability is robust to uncertainties, specifically, large changes in body and feedback parameters.

• Publication year

  2019

• Venue

  Journal of the Royal Society Interface

• Publication date

  2019-08-01

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1098/rsif.2019.0027PMID 31409232PMCID PMC6731497
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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