BSwarm:
Biologically-Plausible Dynamics Model of Insect Swarms
ACM SIGGRAPH/Eurographics
Symposium on Computer Animation'2015, Los Angeles, CA, August 7-9.
Overview of our biologically-driven
insect swarm model (illustrated in 2D view). We highlight different components
of our algorithm used to calculate the position of each insects
at each time step, including two sets of forces: interaction forces and
self-propulsion forces. Interaction forces are represented by
individual-based zones: insects follow forces that are represented in
concentric zones of repulsion, alignment, and attraction to their neighbors. We
use these forces to compute the acceleration and preferred velocity for each
insect, and use velocity obstacles to perform collision avoidance and compute
the actual velocity. The parameter estimation step is performed to compute the
optimal parameters for our model.
A variety of insect swarms can be simulated by our approach:
(left) a swarm of fruitflies in a huge glass box,
(middle) a swarm of male flies compete for a female (the green one), and
(right) a large swarm of migratory locusts passes through a village.
Abstract
We present a biologically plausible dynamics model to simulate swarms
of flying insects. Our formulation, which is based on biological conclusions
and experimental observations, is designed to simulate large insect swarms of
varying densities. We use a hybrid formulation that combines a force-based
model to capture different interactions between the insects with a data-driven
noise model, and computes collision-free trajectories. We introduce a
quantitative metric to evaluate the accuracy of such multi-agent systems and
model the inherent noise. We highlight the performance of our dynamics model
for simulating large flying swarms of midges, fruit fly, locusts and moths. In
practice, our approach can generate many collective behaviors, including
aggregation, migration, phase transition, and escape responses, and we highlight
the benefits over prior methods.
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