Autonomous task sequencing in a robot swarm

About


Can robots cooperate to solve together a complex cognitive problem that none of them can solve alone? A study recently published in Science Robotics shows that a swarm of robots can collectively determine the correct order in which some given tasks must be executed, even if the individual robots comprised in the swarm are unable to do it alone.

Swarm robotics is an approach to robotics inspired by the collective behaviors of social insects: in swarm robotics, a large number of robots are deployed to accomplish a mission that is beyond the capabilities of a single robot and requires that robots cooperate. Think, for example, of a group of robots that cooperate to drag an object that is too heavy for a single robot; or a group of robots that coordinate in order to position themselves so as to monitor a large environment and detect intrusion.

Robot swarms that can perform multiple tasks, one after the other, have already been demonstrated. However, these robot swarms have been developed under the hypothesis that the designer knows, at design time, the order in which tasks must be performed and/or the conditions under which robots must transition from task to task. This article advances the state of the art by demonstrating TS-Swarm: a robot swarm that autonomously sequences tasks at run time and can therefore operate even if the correct order of execution is unknown at design time.

The ability to sequence tasks endows robot swarms with unprecedented autonomy and is an important step towards the uptake of swarm robotics in a range of practical applications. Think for example of searching for survivors after a natural disaster, exploring unknown or hostile environments, or building structures in dangerous sites.


The research was conducted at IRIDIA, the artificial intelligence laboratory of the Université libre de Bruxelles, in the context of the project "DEMIURGE: automatic design of robot swarms," funded by the European Research Council through an ERC Consolidator Grant awarded to Mauro Birattari.

Publication


Read the original article:

L. Garattoni and M. Birattari (2018), Autonomous task sequencing in a robot swarm. Science Robotics 3(20):eaat0430

DOI: 10.1126/scirobotics.aat0430

Authors


Lorenzo Garattoni

Lorenzo Garattoni

A PhD candidate at IRIDIA, Université libre de Bruxelles. He received a Masters's degree in Computer Engineering from Alma mater studiorum Università di Bologna in 2012. His doctoral research focuses on distributed, collective problem solving in swarm robotics and on the automatic generation of solution strategies.

Mauro Birattari

Mauro Birattari

A Senior Research Associate 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 is the principal investigator of the project "DEMIURGE: automatic design of robot swarms," funded by the European Research Council through an ERC Consolidator Grant.

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