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

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.

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