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Artificial Animals for Computer Animation:
Biomechanics, Locomotion, Perception, and Behavior

Doctor of Philosophy, 1996

Xiaoyuan Tu

Department of Computer Science, University of Toronto

Abstract

This thesis develops an artificial life paradigm for computer graphics animation. Animals in their natural habitats have presented a long-standing and difficult challenge to animators. We propose a framework for achieving the intricacy of animal motion and behavior evident in certain natural ecosystems, with minimal animator intervention.

Our approach is to construct artificial animals. We create self-animating, autonomous agents which emulate the realistic appearance, movement, and behavior of individual animals, as well as the patterns of social behavior evident in groups of animals. Our computational models achieve this by capturing the essential characteristics common to all biological creatures--biomechanics, locomotion, perception, and behavior.

To validate our framework, we have implemented a virtual marine world inhabited by a variety of realistic artificial fishes. Each artificial fish is a functional autonomous agent. It has a physics-based, deformable body actuated by internal muscles, sensors such as eyes, and a brain with perception, motor, and behavior control centers. It swims hydrodynamically in simulated water through the controlled coordination of its muscle actions. Artificial fishes exhibit a repertoire of behaviors. They explore their habitat in search of food, navigate around obstacles, contend with predators, and indulge in courtship rituals to secure mates. Like their natural counterparts, their behavior is based on their perception of the dynamic environment and their internal motivations.

Since the behavior of artificial fishes is adaptive to their virtual habitat, their detailed motions need not be keyframed nor scripted. This thesis therefore demonstrates a powerful approach to computer animation in which the animator plays the role of a nature cinematographer, rather than the more conventional role of a graphical model puppeteer. Our work not only achieves behavioral animation of unprecedented complexity, but it also provides an interesting experimental domain for related research disciplines in which functional, artificial animals can serve as autonomous virtual robots.


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