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.
['Eric Aaron', 'Harold C. Sun', 'Franjo Ivancic', 'Dimitris N. Metaxas']
A hybrid dynamical systems approach to intelligent low-level navigation