Artificial Life Laboratory, Graz, Austria

Honeybees are social insects which exhibit a wide range of collective behaviour. This leads to the emergence of abilities that single individuals wouldn’t be capable of. For example, groups of bees are able to collaboratively find a spot with optimal temperature while single bees fail at this task. We are currently conducting an in-depth investigating of this special aspect of swarm behavior in an FWF-funded research project (FWF – P 19478-B16).

REBODIMENT will relate closely to this project, but the swarm system will be examined from a new point of view. We will exploit the results retrieved from behavioural observations to precisely recreate swarms of bees in simulations (computer models) and emulations (robots) and to observe them “from within”. With this approach, we expect to deepen our knowledge about the dependency between individual and collective behaviour and the influence of the physical embodiment on the relationship between them.

We will design a mathematical model which describes the behaviour of a swarm of bodi- and physicless individuals (agents) with the help of simple differential equations. A multi-agent model will allow us to deliberately simulate bees as bodiless agents without physical environment or as embodied agents which interact with one another and with a simplified simulated physical environment. For an implementation of the behavioural algorithms under physically realistic conditions we will resort to ePuck robots which we will extend by two temperature sensors located at the ends of two antennae. Similar to the bees in the current project, these ThermoBots will move in an arena on the ground of which we will establish a thermal gradient. Due to the comparable embodiment (antennae), the perception of the thermal gradient will be similar to the one that bees experience. We expect to identify a core algorithm in all forms of embodiment which acts as their common foundation of behaviour, while a set of additional, specific parameters adapt the core algorithm to the ultimate embodiment.

Additionally, we will develop a new paradigm for programming robotic swarms based on the variability of individual behaviour. This will allow us to control a swarm’s ultimate behaviour by composing it from individuals with different behavioural traits.

The results of the projected experiments and the introduction of the new concept for programming swarms will contribute to the solution of technical problems which robot engineers haven’t been able to solve so far. Additionally, we expect to improve our knowledge about the mechanisms that govern the collective behaviour of biological organisms on the most fundamental level.