Evolving teamwork and role-allocation with real robots

Authors:
Matt Quinn;Lincoln Smith;Giles Mayley;Phil Husbands
Affiliations:
Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, BN1 9QG, U.K.;Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, BN1 9QG, U.K.;Mathematique Appliqué S.A. Brighton Innovation Centre, University of Sussex, Brighton BN1 9QG, U.K.;Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, BN1 9QG, U.K.
Venue:
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Year:
2002

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Abstract

We report on recent work in which we employed artificial evolution to design neural network controllers for small, homogeneous teams of mobile autonomous robots. The robots are evolved to perform a formation movement task from random starting positions, equipped only with infrared sensors. The dual constraints of homogeneity and minimal sensors make this a non-trivial task. We describe the behaviour of a successful evolved team in which robots adopt and maintain functionally distinct roles in order to achieve the task. We believe this to be the first example of the use of artificial evolution to design coordinated, cooperative behaviour for real robots.