2019
DOI: 10.1098/rsif.2019.0027
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A controller for walking derived from how humans recover from perturbations

Abstract: 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 … Show more

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Cited by 37 publications
(61 citation statements)
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“…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.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…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.…”
Section: Methodsmentioning
confidence: 99%
“…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 .…”
Section: Methodsmentioning
confidence: 99%
“…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.…”
Section: Introductionmentioning
confidence: 99%
“…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.…”
mentioning
confidence: 99%