Exoskeleton Active Walking Assistance Control Framework Based on Frequency Adaptive Dynamics Movement Primitives.

Frontiers in Neurorobotics
Shiyin QiuXin Wang

Abstract

This paper introduces a novel exoskeleton active walking assistance control framework based on frequency adaptive dynamics movement primitives (FADMPs). The FADMPs proposed in this paper is an online learning and prediction algorithm which is able to online estimate the fundamental frequency of human joint trajectory, learn the shape of joint trajectory and predict the future joint trajectory during walking. The proposed active walking assistance control framework based on FADMPs is a model-based controller which relies on the human joint torque estimation. The assistance torque provided by exoskeleton is estimated by human lower limb inverse dynamics model which is sensitive to the noise in the joint motion trajectory. To estimate a smooth joint torque profile, the joint motion trajectory must be filtered first by a lowpass filter. However, lowpass filter will introduce an inevitable phase delay in the filtered trajectory. Both simulations and experiments in this paper show that the phase delay has a significant effect on the performance of exoskeleton active assistance. The active assistant control framework based on FADMPs aims at improving the performance of active assistance control by compensating the phase delay. Both si...Continue Reading

References

Sep 2, 2011·Medical & Biological Engineering & Computing·Renaud RonsseAuke Jan Ijspeert
Jan 1, 2011·Topics in Spinal Cord Injury Rehabilitation·Hugo A QuinteroMichael Goldfarb
Oct 23, 2012·American Journal of Physical Medicine & Rehabilitation·Alberto EsquenaziMichael Saulino
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Jul 27, 2018·IEEE Transactions on Neural Networks and Learning Systems·Chenguang YangZhijun Li
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Software Mentioned

FADMPS
Matlab
Simscape
PSAO
Simulink
AO

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