In group-living animals, aggregation favours interactions as well as information exchanges between individuals, and allows thus the emergence of complex collective behaviors. In previous works, a model of a self-enhanced aggregation was deduced from experiments with the cockroach Blattella germanica. In this work, this model was implemented in micro-robots Alice and successfully reproduced the agregation dynamics observed in a group of cockroaches. We showed that this aggregation process, based on a small set of simple behavioral rules and interactions among individuals, can be used by the group of robots to select collectively an aggregation site among two identical or different shelters. Moreover, we showed that the aggregation mechanism allows the robots as a group to estimate the size of each shelter during the collective decision-making process, a capacity which is not explicitly coded at the individual level but that simply emerges from the aggregation behaviour.  or collective defense ). Among all these self-organized behaviours, aggregation is one of the simplest. But it is also one of the most useful. For instance, it allows an individual to transmit an information in a very efficient way to many other conspecifics at the same time. It thus favours recruitment processes during food source exploitation  or territory defense . Aggregation also facilitates the interactions among individuals, leading to complex collective behaviors such as nest construction , nest-site selection  or traffic regulation . To sum up, aggregation is a step toward much more complex collective behaviours because it favours interactions and information exchanges among individuals, leading to the emergence of complex and functional self-organized structures. As such it plays a keyrole in the evolution of cooperation in animal societies .