Automatic design of stigmergy-based behaviours


Stigmergy is a form of indirect communication and coordination in which individuals influence their peers by modifying the environment in various ways, including rearranging objects in space and releasing chemicals. For example, some ant species lay pheromone trails to efficiently navigate between food sources and nests.

Besides being used by social animals, stigmergy has also inspired the development of algorithms for combinatorial optimisation and multi-robot systems. In swarm robotics, collective behaviours based on stigmergy have always been designed manually, which is time consuming, costly, hardly repeatable, and depends on the expertise of the designer.

In the article, we show that stigmergy-based behaviours can be produced via automatic design: an optimisation process based on simulations generates collective behaviours for a group of robots that can lay and sense artificial pheromones. To conduct our study, we conceived Habanero: an automatic design method that belongs to the family of modular methods AutoMoDe.

We used Habanero to generate control software for a swarm of eight e-puck robots in four missions: AGGREGATION, DECISION MAKING, RENDEZVOUS POINT, and STOP. The robots had to rely on stigmergy-based coordination to succesfully perform these missions.

The results of our experiments indicate that the collective behaviours designed automatically are as good as—and in some cases better than—those produced manually. By taking advantage of pheromone-based stigmergy, the automatic design process generated collective behaviours that exhibit spatial organisation, memory, and communication.

With Habanero we demonstrated that it is possible to generate pheromone-based collective behaviours through an automatic process that is repeatable and generally applicable. We contend that this result can motivate further research to overcome limitations of the currently available solutions to implement pheromone-based stigmergy in robotics.

This work is a core contribution of the DEMIURGE project, funded by the European Research Council via an ERC Consolidator Grant awarded to Mauro Birattari of IRIDIA, the artificial intelligence laboratory of the ULB.


Read the original article:

Muhammad Salman, David Garzón Ramos, and Mauro Birattari* (2024)
Automatic design of stigmergy-based behaviours for robot swarms.
Communications Engineering, 3:30.

DOI: 10.1038/s44172-024-00175-7

Download the PDF file

These authors contributed equally: Muhammad Salman and David Garzón Ramos
*Corresponding author: Mauro Birattari <>


Muhammad Salman

Muhammad Salman

An astronomical instrumentation engineer specializing in robotics and control. Currently based at the Institute of Astronomy, KU Leuven, Belgium, he is concurrently pursuing a PhD in automatic design of robot swarms at Université libre de Bruxelles, Belgium. His primary focus lies in contributing to astronomical telescope projects, notably METIS (one of the three first light instruments of the Extremely Large Telescope, ELT) and NOTT/ASGARD (a visitor instrument at VLT Paranal, Chile). Beyond his work in astronomy, Muhammad Salman possesses a background in control systems design, development, and implementation of both single and multi-robot systems.

David Garzón Ramos

David Garzón Ramos

A PhD candidate at IRIDIA, Université libre de Bruxelles. He received a Master's degree in Automation and Robotics from Universidad Politécnica de Madrid, Spain, in 2016. His research interests are swarm robotics, the optimization-based design of control software, the automatic design of collective behaviors, and the Robot Operating System (ROS). He actively contributes to the communication and popularization of swarm robotics research.

Mauro Birattari

Mauro Birattari

A Research Director of the Belgian Fonds de la Recherche Scientifique—FNRS at IRIDIA, Université libre de Bruxelles. He received a Master's degree in Electrical and Electronic Engineering from Politecnico di Milano in 1997 and a doctoral degree in Information Technologies from the Faculty of Engineering of the Université libre de Bruxelles in 2004. His research focuses on swarm intelligence, collective robotics, machine learning, and on the application of artificial intelligence techniques to the automatic design of algorithms.

Dr. Birattari was the principal investigator of the project "DEMIURGE: automatic design of robot swarms," funded by the European Research Council through an ERC Consolidator Grant.


For further information, please contact us at: