Designing and implementing artificial self-organizing systems is a
challenging task since they typically behave non-intuitive and only little
theoretical foundations exist. Predicting a system of many components with a
huge amount of interactions is beyond human skills. The currently common use
of simulations for design support is not satisfying, as it is time-consuming
and the results are most likely suboptimal.
In this work, we present the derivation of an analytical, time-, and
space-continuous model for a swarm of autonomous robots based on the
Fokker-Planck equation. While the motion model is in most parts physically
motivated, the communication model is based on a heuristic approach.
A showcase application to a recently proposed scenario of collective
perception in a huge swarm of robots with very limited abilities is given
and the simulation results are compared to the model. Despite the high level
of abstraction, the prediction discrepancies are small and the parameters
can be mapped one-to-one from the model to the control algorithm. Finally,
we give an outlook on the capabilities of the proposed model, discuss its
limitations, and suggest an improvement that could reduce the number of
empirically determined parameters.
(see doi.ieeecomputersociety.org/10.1109/SASO.2007.3 [2])
Links:
[1] http://zool33.uni-graz.at/artlife/hamann
[2] http://doi.ieeecomputersociety.org/10.1109/SASO.2007.3
[3] http://zool33.uni-graz.at/artlife/sites/default/files/hamannSaso07.pdf
[4] http://zool33.uni-graz.at/artlife/i-swarm