Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and...

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Main Authors:	Duarte, Miguel, Costa, Vasco, Gomes, Jorge, Rodrigues, Tiago, Silva, Fernando, Oliveira, Sancho Moura, Christensen, Anders Lyhne
Format:	Online
Language:	English
Published:	Public Library of Science 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801206/

id	pubmed-4801206
recordtype	oai_dc
spelling	pubmed-48012062016-03-23 Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots Duarte, Miguel Costa, Vasco Gomes, Jorge Rodrigues, Tiago Silva, Fernando Oliveira, Sancho Moura Christensen, Anders Lyhne Research Article Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. Public Library of Science 2016-03-21 /pmc/articles/PMC4801206/ /pubmed/26999614 http://dx.doi.org/10.1371/journal.pone.0151834 Text en © 2016 Duarte et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Duarte, Miguel Costa, Vasco Gomes, Jorge Rodrigues, Tiago Silva, Fernando Oliveira, Sancho Moura Christensen, Anders Lyhne
spellingShingle	Duarte, Miguel Costa, Vasco Gomes, Jorge Rodrigues, Tiago Silva, Fernando Oliveira, Sancho Moura Christensen, Anders Lyhne Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
author_facet	Duarte, Miguel Costa, Vasco Gomes, Jorge Rodrigues, Tiago Silva, Fernando Oliveira, Sancho Moura Christensen, Anders Lyhne
author_sort	Duarte, Miguel
title	Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
title_short	Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
title_full	Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
title_fullStr	Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
title_full_unstemmed	Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
title_sort	evolution of collective behaviors for a real swarm of aquatic surface robots
description	Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.
publisher	Public Library of Science
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801206/
_version_	1613555499857346560

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

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