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Proceedings Paper

Connectionist model of three-link pendulum for NN-simulation
Author(s): Mehmet Celenk; Ivan Chang
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Paper Abstract

Numerical simulation of physics-based models has been applied to computer graphics animation due to the high degree of realism and automation it offers. However, the high cost of computation with numerical simulation is a major disadvantage compared to the more efficient geometric- based approaches. This paper shows a different approach to creating realistic simulations by using neural networks to observe and learn the dynamics of physics-based models. It also facilitates a means to solve the control problem associated with physics-based models efficiently and generate goal-based simulations. In the implementation, a regularization network is selected with sigmoidal units to emulate the dynamics of a three-linked pendulum subjected to a gravitational field. It is demonstrated by computer simulation that a feed-forward neural network is able to animate the motion of a pendulum using a limited set of data.

Paper Details

Date Published: 30 March 2000
PDF: 8 pages
Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380585
Show Author Affiliations
Mehmet Celenk, Ohio Univ. (United States)
Ivan Chang, Ohio Univ. (United States)

Published in SPIE Proceedings Vol. 4055:
Applications and Science of Computational Intelligence III
Kevin L. Priddy; Paul E. Keller; David B. Fogel, Editor(s)

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