Abstract
Swarm robotic systems are particular types of multi-robot systems, which consist of many homogeneous autonomous robots without any type of global controllers. Since a robotic swarm is controlled by an emergent way of many interactions with the other robots or an environment, such as a result of self-organization, robot learning or artificial evolution, no method has been known to grasp the swarm behavior in a practical sense, according to the best of our knowledge. In this paper, we propose a novel method for analyzing the swarm behavior for SRS based on clustering the complex network associated with robots in the cooperative package pushing problem. We demonstrate that this technique enables us to find several robot subgroups each of which may have a certain functional role emerged in a robotic swarm as a robotic community structure by the result of clustering.
