On self-organised aggregation dynamics in swarms of robots with informed robots

In this paper, we use simulated swarms of robots to further explore the aggregation dynamics generated by these simple individual mechanisms. Our objective is to study the introduction of "informed robots", and to study how many of these are needed to direct the aggregation process toward a pre-defined site among those available in the environment. Informed robots are members of a group that selectively avoid the site/s where no aggregate should emerge, and stop only on the experimenter predefined site/s for aggregation. We study the aggregation process with informed robots in three different scenarios: two that are morphologically symmetric, whereby the different types of aggregation site are equally represented in the environment; and an asymmetric scenario, whereby the target site has an area that is half the area of the sites that should be avoided. We first show what happens when no robot in the swarm is informed: in symmetric environments, the swarm is able to break the symmetry and aggregates on one of the two types of site at random, not necessarily on the target site, while in the asymmetric environment, the swarm tends to aggregate on the sites that are most represented in terms of area. As a further valuable contribution of this study, we provide analytical results by studying a system of Ordinary Differential Equations' (ODEs) that is an extension of a well known model. Using this model, we show how, for certain values of the parameters, the model can predict the dynamics observed with simulated robots in one of the two symmetric scenarios.
Comment: Submitted Neural Computing and Applications