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Composition of Dynamical Systems for Estimation of Human Body Dynamics

Ganesh, Sumitra and Ames, Aaron D. and Bajcsy, Ruzena (2007) Composition of Dynamical Systems for Estimation of Human Body Dynamics. In: Hybrid Systems: Computation and Control. Lecture Notes in Computer Science. No.4416. Springer , Berlin, pp. 702-705. ISBN 978-3-540-71492-7. https://resolver.caltech.edu/CaltechAUTHORS:20190821-103851149

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Abstract

This paper addresses the problem of estimating human body dynamics from 3-D visual data. That is, our goal is to estimate the state of the system, joint angle trajectories and velocities, and the control required to produce the observed motion from indirect noisy measurements of the joint angles. For a two-link chain in the human body, we show how two independent spherical pendulums can be composed to create a behaviorally equivalent double spherical pendulum. Therefore, the estimation problem can be solved in parallel for the low-dimensional spherical pendulum systems and the composition result can be used to arrive at estimates for the higher dimensional double spherical pendulum system. We demonstrate our methods on motion capture data of human arm motion.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-3-540-71493-4_65DOIArticle
ORCID:
AuthorORCID
Ames, Aaron D.0000-0003-0848-3177
Additional Information:© 2007 Springer Berlin Heidelberg.
Subject Keywords:Joint Angle; Open Chain; Motion Capture Data; Composition Result; Auxiliary Particle
Series Name:Lecture Notes in Computer Science
Issue or Number:4416
Record Number:CaltechAUTHORS:20190821-103851149
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190821-103851149
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:98074
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:21 Aug 2019 20:12
Last Modified:03 Oct 2019 21:37

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