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Animated characters may exhibit several kinds of dynamic intelligence when performing low-level navigation (i.e., navigation on a local perceptual scale): They decide among different modes of behavior, selectively discriminate entities in the world around them, perform obstacle avoidance, etc. In this paper, we present a hybrid dynamical system model of low-level navigation that accounts for the above-mentioned kinds of intelligence. In so doing, the model illustrates general ideas about how a hybrid systems perspective can influence and simplify such reactive/behavioral modeling for multi-agent systems. In addition, we directly employed our formal hybrid system model to generate animations that illustrate our navigation strategies. Overall, our results suggest that hierarchical hybrid systems may provide a natural framework for modeling elements of intelligent animated actors.
Aaron, E., Sun, H., Ivancic, F., & Metaxas, D. (2002). A Hybrid Dynamical Systems Approach to Intelligent Low-Level Navigation. Retrieved from https://repository.upenn.edu/hms/32
Date Posted: 16 July 2007
This document has been peer reviewed.