Connectionist model of three-link pendulum for NN-simulation

Mehmet Celenk; Ivan Chang

doi:10.1117/12.380585

30 March 2000 Connectionist model of three-link pendulum for NN-simulation

Mehmet Celenk, Ivan Chang

Proceedings Volume 4055, Applications and Science of Computational Intelligence III; (2000) https://doi.org/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.

Citation Download Citation

Mehmet Celenk and Ivan Chang "Connectionist model of three-link pendulum for NN-simulation", Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); https://doi.org/10.1117/12.380585

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