A controller for walking derived from how humans recover from perturbations

Abstract

<jats:p>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.</jats:p>

Exploration-based learning of a stabilizing controller predicts locomotor adaptation

“…e.g., walking on a split-belt treadmill instead of a regular treadmill. The values of these control variables on each step are decided by a discrete controller, as described below, derived from our prior human experiments [26][27][28] . Let us denote the two control variables together by the variable u.…”

“…The three terms make the controller a discrete PID controller (proportional-integral-derivative). The default values for the control gain matrix K are obtained by fitting the dynamics of the model biped to the step to step map of normal human walking on a treadmill [26][27][28]62 .…”

Rhythmic auditory stimuli modulate movement recovery in response to perturbation during locomotion

“…leg retraction) to counteract terrain perturbations during running ( Muller et al, 2016 ; Seyfarth et al, 2003 ; Daley et al, 2007 ). However, reflex-mediated feedback control (of, for example, foot placement: Ignasiak et al, 2019 ; Joshi and Srinivasan, 2019 ) may be predominantly involved in locomotion at slow speeds ( Marigold and Patla, 2005 ). Furthermore, it remains unclear how these mechanisms vary across different perturbation types and sizes.…”

Altered active control of step width in response to mediolateral leg perturbations while walking

“…Recent 2-dimensional simulations have demonstrated that in the sagittal plane, passive dynamics can produce significant correlations between pelvis motion and step length without need for active control 5 . While similar 3-dimensional simulations require active control to ensure frontal plane gait stability 6,7 , passive dynamics surely contributes to frontal plane motion. This limitation of correlation-based methods has been widely acknowledged 2,3,8 , and has motivated the use of other experimental methods to provide more direct evidence for active control of step width-revealing the existence of clear within-step control.…”