Connectionist model of three-link pendulum for NN-simulation
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.
- Publication:
-
Applications and Science of Computational Intelligence III
- Pub Date:
- March 2000
- DOI:
- 10.1117/12.380585
- Bibcode:
- 2000SPIE.4055...28C