Inherent Noise-Aware Insect Swarm Simulation

dc.contributor.authorWang, Xinjieen_US
dc.contributor.authorJin, Xiaogangen_US
dc.contributor.authorDeng, Zhigangen_US
dc.contributor.authorZhou, Linlingen_US
dc.contributor.editorOliver Deussen and Hao (Richard) Zhangen_US
dc.date.accessioned2015-03-03T12:44:11Z
dc.date.available2015-03-03T12:44:11Z
dc.date.issued2014en_US
dc.description.abstractCollective behaviour of winged insects is a wondrous and familiar phenomenon in the real world. In this paper, we introduce a highly efficient field-based approach to simulate various insect swarms. Its core idea is to construct a smooth yet noise-aware governing velocity field that can be further decomposed into two sub-fields: (i) a divergence-free curl-noise field to model noise-induced movements of individual insects in a swarm, and (ii) an enhanced global velocity field to control navigational paths in a complex environment along which all the insects in a swarm fly. Through simulation experiments and comparisons with existing crowd simulation approaches, we demonstrate that our approach is effective to simulate various insect swarm behaviours including aggregation, positive phototaxis, sedation, mass-migrating, and so on. Besides its high efficiency, our approach is very friendly to parallel implementation on GPUs (e.g. the speedup achieved through GPU acceleration is higher than 50 if the number of simulated insects is more than 10 000 on an off-the-shelf computer). Our approach is the first multi-agent modelling system that introduces curl-noise into agents' velocity field and uses its non-scattering nature to maintain non-colliding movements in 3D crowd simulation.Collective behavior of winged insects is a wondrous and familiar phenomenon in the real world. In this paper, we introduce a highly efficient field-based approach to simulate various insect swarms. Its core idea is to construct a smooth yet noise-aware governing velocity field that can be further decomposed into two sub-fields: (i) a divergence-free curl noise field to model noise-induced movements of individual insects in a swarm, and (ii) an enhanced global velocity field to control navigational paths in a complex environment along which all the insects in a swarm fly.en_US
dc.description.number6
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume33
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12277en_US
dc.publisherThe Eurographics Association and John Wiley and Sons Ltd.en_US
dc.titleInherent Noise-Aware Insect Swarm Simulationen_US
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