30 March 2000 Connectionist model of three-link pendulum for NN-simulation
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Proceedings Volume 4055, Applications and Science of Computational Intelligence III; (2000); doi: 10.1117/12.380585
Event: AeroSense 2000, 2000, Orlando, FL, United States
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.
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Mehmet Celenk, Ivan Chang, "Connectionist model of three-link pendulum for NN-simulation", Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380585; https://doi.org/10.1117/12.380585
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KEYWORDS
Neural networks

Data modeling

Motion models

Computer simulations

Numerical simulations

Computer graphics

Kinematics

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