Adaptively Coordinating Heterogeneous Robot Teams through Asynchronous Situated Coevolution

Authors:
Abraham Prieto;Francisco Bellas;Richard J. Duro
Affiliations:
Integrated Group for Engineering Research, Universidade da Coruña, Spain;Integrated Group for Engineering Research, Universidade da Coruña, Spain;Integrated Group for Engineering Research, Universidade da Coruña, Spain
Venue:
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Year:
2009

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Abstract

Adapting to changing situations and objectives and selforganazing without a central controller in order to achieve an objective has become one of the main challenges in the design and operation of multirobot systems. The Asynchronous Situated Coevolution (ASiCO) algorithm has been successfully applied in surveillance tasks defined by just one global objective. In this paper we present the results obtained with ASiCO in more complex multirobot problems with several objectives that require a heterogeneous population of robot controllers that autonomously distribute the tasks. The paper focuses on the benefits of evolving an affinity coefficient that characterizes the individual genotypes.