Analyzing collective behavior in evolutionary swarm robotic systems based on an ethological approach

Abstract

Swarm robotic systems are a type of multi-robot systems which generally consist of many homogeneous autonomous robots without any type of global controllers. Swarm robotics aims at designing desired collective behaviors through many interactions with other robots or their environment. Since a robotic swarm is controlled by an emergent way such as a result of self-organization by using robot learning or artificial evolution, no method has been known to grasp the macroscopic collective behavior in a practical sense, according to the best of our knowledge. In this paper, we propose a novel method for analyzing the collective behavior by introducing the concept of behavioral sequence, which stems from ethology. Analysis about behavioral sequence reveals the transition of robot's action from the viewpoint of specialization and helps us to understand the role of subgroups in a robotic swarm. Applying this method, we observe collective behavior in a foraging task of autonomous mobile robots.