BEECLUST: A Swarm Algorithm Derived from Honeybees. Derivation of the Algorithm, Analysis by Mathematical Models and Implementation on a Robot Swarm

Thomas Schmickl, Heiko Hamann
Bio-inspired Computing and Networking, Yang Xiao (editor) (2011), 95-137


We demonstrate the derivation of a powerful and simple, as well as robust
and flexible algorithm for a swarm robotic system derived from
observations of honeybees’ collective behavior. We show how such observations
made in a natural system can be translated into an abstract
representation of behavior (algorithm) working in the sensor-actor world
of small autonomous robots. By developing several mathematical models
of varying complexity, the global features of the swarm system are
investigated. These models support us in interpreting the ultimate reasons
of the observed collective swarm behavior and they allow us to
predict the swarm’s behavior in novel environmental conditions. In turn
these predictions serve as inspiration for new experimental setups with
both, the natural system (honeybees and other social insects) as well as
the robotic swarm. This way, a deeper understanding of the complex
properties of the collective algorithm, taking place in the bees and in
the robots, is achieved.