Fall detection in walking robots by multi-way principal component analysis

Journal article (2008)
Department
Biomechanical Engineering (AS) (TU Delft)
Copyright: © 2008 Cambridge University Press
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Published Date

08-05-2008

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Source:

Robotica, 27 (2009)

Faculty

Applied Sciences

Department

Biomechanical Engineering

Abstract

Large disturbances can cause a biped to fall. If an upcoming fall can be detected, damage can be minimized or the fall can be prevented. We introduce the multi-way principal component analysis (MPCA) method for the detection of upcoming falls. We study the detection capability of the MPCA method in a simulation study with the simplest walking model. The results of this study showthat the MPCA method is able to predict a fall up to four steps in advance in the case of single disturbances. In the case of random disturbances the MPCA method has a successful detection probability of up to 90%.

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