Hybrid System Models of Navigation Strategies for Games and Animations

Aaron, Eric; Ivančić, Franjo; Metaxas, Dimitris N.

doi:10.1007/3-540-45873-5_4

Cited by 11 publications

(10 citation statements)

References 23 publications

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“…Our experience shows that CHARON simulations of formally specified animation systems often take longer than simulations of equivalent systems coded outside of CHARON [3]. Briefly, we believe the reasons for this are largely related to the differences in primary goals of the two disciplines, hybrid systems and animation.…”

Section: Simulationmentioning

confidence: 98%

“…It is not necessarily obvious, however, how to represent such high-level strategies in a hybrid automaton model that retains the reactive/behavioral flavor of our low-level navigation system. (See [3] for discussion. )…”

Section: Simulationmentioning

confidence: 99%

“…It is a novel application of theoretical hybrid system models from both the hybrid systems [3] and animation perspectives.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid dynamical systems approach to intelligent low-level navigation

Aaron

Sun

Ivančić

et al.

Proceedings of Computer Animation 2002 (CA 2002)

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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. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/hms/32 A Hybrid Dynamical Systems Approach to Intelligent Low-Level Navigation

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Section: Simulationmentioning

confidence: 98%

Section: Simulationmentioning

confidence: 99%

See 1 more Smart Citation

A hybrid dynamical systems approach to intelligent low-level navigation

Aaron

Sun

Ivančić

et al.

Proceedings of Computer Animation 2002 (CA 2002)

View full text Add to dashboard Cite

show abstract

“…These systems provide some specification tools similar to our EquationalReset scheme; however, they appear to provide little or no support for specifying the kinds of temporal relationships that can be expressed using our ConditionalTermination and TemporalProjection schemata. Applications of Charon to computer animation are discussed in [Aaron, et al 2001] and [Aaron, et al 2002]. This work uses Charon to model low-level and high-level navigation strategies for virtual agents operating in a two-dimensional world.…”

Section: Related Workmentioning

confidence: 99%

“…Some use program scheme instantiation and transformation techniques that are similar to the methods of our implementation rules; however, the applications are generally quite different. SciNapse uses a knowledge base of transformation rules implemented in Mathematica to generate programs that solve partial differential equations [Kant, 1993], [Akers et al, 1998]. Amphion uses deductive synthesis to generate programs utilizing libraries of astronomical software [Lowry et al, 1994].…”

Section: Related Workmentioning

confidence: 99%