Abstract

The principles underlying smooth and effortless human walking while maintaining stability as well as the ability to quickly respond to unexpected perturbations result from a plethora of well-balanced parameters, most of them yet to be determined. In this paper, we investigate criteria that may be useful for benchmarking stability properties of human walking. We perform dynamic reconstructions of human walking motions of unimpaired subjects and subjects walking with transfemoral prostheses from motion capture recordings using optimal control. We aim at revealing subject-specific strategies in applying dynamics in order to maintain steady gait considering irregularities such as deviating gait patterns or asymmetric body segment properties. We identify foot placement with respect to the Instantaneous Capture Point as the strategy globally applied by the subjects to obtain steady gait and propose the Residual Orbital Energy as a measure allowing for benchmarking human-like gait toward confident vs. cautious gait.

Highlights

  • Human and human-like walking motions form an important and challenging class of motions with respect to dynamics and control

  • We have applied them to the walking motions of two unimpaired subjects and one subject walking with a transfemoral prosthesis which have been reconstructed from motion capture recordings using multibody dynamics and optimal control methods

  • The reconstructed walking motions have been analyzed for their dynamics and findings are gathered on how unbalanced habitual gait patterns can lead to irregular walking motions

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Summary

Introduction

Human and human-like walking motions form an important and challenging class of motions with respect to dynamics and control. In the KoroiBot project, which studied human locomotion with the intention to improve walking qualities of humanoid robots, Benchmarking Stability: Dynamics, Foot Placement we have distinguished three different groups of key performance indicators (KPIs) to benchmark locomotion (see Schubert et al, 2014). The third group contains high level KPIs and aims to asses to which amount motions of robots are human-like, a concept that can be extended to investigate the effect of impairments or assistive devices to human walking motions. This evaluation is, to some extent related to the technical performance evaluation on the lower level

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