Sorting in Swarm Robots Using Communication-Based Cluster Size Estimation

Inspired by sorting behaviors of social insects, we are interested in sorting by robot swarms using only local information and hence achieving high degrees of robustness and scalability. In this work, we propose a gossip-based sorting method which allows two swarms of simple homogeneous autonomous robots to sort themselves in two not pre-assigned areas. Key feature of this method is the estimation of cluster sizes based on communication that allows to determine the local majority. In a series of simulation experiments, we show the effectiveness of the approach and investigate the influence of different swarm sizes.