Deep Learning Based Model Identification System Exploits the Modular Structure of a Bio-Inspired Posture Control Model for Humans and Humanoids
Machine Learning
2021-03-08 v1
Abstract
This work presents a system identification procedure based on Convolutional Neural Networks (CNN) for human posture control using the DEC (Disturbance Estimation and Compensation) parametric model. The modular structure of the proposed control model inspired the design of a modular identification procedure, in the sense that the same neural network is used to identify the parameters of the modules controlling different degrees of freedom. In this way the presented examples of body sway induced by external stimuli provide several training samples at once
Cite
@article{arxiv.2102.02536,
title = {Deep Learning Based Model Identification System Exploits the Modular Structure of a Bio-Inspired Posture Control Model for Humans and Humanoids},
author = {Vittorio Lippi},
journal= {arXiv preprint arXiv:2102.02536},
year = {2021}
}
Comments
Presented at ICPRAM 2021, International Conference on Pattern Recognition Applications and Methods