Sorting in Swarm Robots Using Communication-Based Cluster Size Estimation Hongli Ding and Heiko Hamann Department of Computer Science, University of Paderborn, Paderborn, Germany hongli.ding@uni-paderborn.de, heiko.hamann@uni-paderborn.de April 18, 2015 Abstract Inspired by sorting behaviors of social insects, we are interested in sorting by robot swarms using only local information and hence achiev- ing high degrees of robustness and scalability. In this work, we propose a gossip-based sorting method which allows two swarms of simple homo- geneous 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. 1 Introduction Recent research shows that social insects sort their brood in sophisticated pat- terns. These well-organized brood sorting patterns emerge spontaneously from dynamic interactions during the process of depositing and removing brood. Dur- ing this sorting process, no specified spatial plans or any global representation is required, nor any hierarchical decisions are made [1]. By interacting among other individuals and with the environment, individuals act following their own goals and knowledge about the environment. The collective behavior on the group level emerges from the sum over all individual decisions, actions, and the interactions among individuals and the environment. The sorting system of social insects has many attractive features such as scalability, flexibility, and robustness. Abstract models based on sorting behaviors of social insects have been applied in many areas such as search, collective sorting, data mining, nu- meric data analysis, and graph partitioning [7]. Inspired by how ants and honey bees sort their broods, we are interested in how to implement these natural sorting behaviors and strategies in a swarm of robots. We simplify the sorting task to sorting robots instead of objects. This preliminary work aims at sorting 1