Governing the swarm: Controlling a bio-hybrid society of bees & robots with computational feedback loops
Martin Stefanec, Martina Szopek, Thomas Schmickl, Rob Mills
- Year
- 2017
- Citations
- 19
Abstract
Bio-hybrid systems in which living organisms interact and self-organize with multi-robot systems are a novel approach in engineering and biology. We show here how a group of honeybees and robots can interact in collective decision making and how computer code that adds feedback loops to the system may affect the global system properties. This study contains a series of experiments with living honeybees and robots as well as a cellular-automaton inspired model that is simple, yet still in good agreement with the empirical findings presented here. Using this model, we explore the most likely candidates for local parameters in the proximate mechanisms of the animals, thus further the understanding of this natural system in a context that is relevant for such bio-hybrid manifestations. We identify positive feedback based on bee-to-bee collision and temperature as an important factor governing collective decision making and found the stopping probability after close-encounters among bees as a crucial local parameter. This study is the first step towards using computer and robotic technology to monitor and control complex animal societies like honeybees.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002