The present paper presents a methodology to identify regularities in motion trajectories and encode them into a reduced order model. The model has been developed for being trained with real data captured during the execution of complex and articulated motions, having several phases each. The presented model possesses relevant features that make it adequate for motion representation, among these we will discuss: stability, generalization, optimization, adaptation and external dynamic synchronization. Practical examples taken from ball throwing and catching will be given.
A regression model for Digital Representation of Juggling
AVIZZANO, Carlo Alberto;LIPPI, Vittorio
2011-01-01
Abstract
The present paper presents a methodology to identify regularities in motion trajectories and encode them into a reduced order model. The model has been developed for being trained with real data captured during the execution of complex and articulated motions, having several phases each. The presented model possesses relevant features that make it adequate for motion representation, among these we will discuss: stability, generalization, optimization, adaptation and external dynamic synchronization. Practical examples taken from ball throwing and catching will be given.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
