Publicação em atas de evento científico
Cooperative coevolution of control for a real multirobot system
Jorge Gomes (Gomes, J.); Miguel Duarte (Duarte, M.); Pedro Mariano (Mariano, P.); Anders Christensen (Christensen, A. L.);
Parallel Problem Solving from Nature – PPSN XIV. Lecture Notes in Computer Science
Ano (publicação definitiva)
2016
Língua
Inglês
País
Alemanha
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Abstract/Resumo
The potential of cooperative coevolutionary algorithms (CCEAs) as a tool for evolving control for heterogeneous multirobot teams has been shown in several previous works. The vast majority of these works have, however, been confined to simulation-based experiments. In this paper, we present one of the first demonstrations of a real multirobot system, operating outside laboratory conditions, with controllers synthesised by CCEAs. We evolve control for an aquatic multirobot system that has to perform a cooperative predator-prey pursuit task. The evolved controllers are transferred to real hardware, and their performance is assessed in a non-controlled outdoor environment. Two approaches are used to evolve control: a standard fitness-driven CCEA, and novelty-driven coevolution. We find that both approaches are able to evolve teams that transfer successfully to the real robots. Novelty-driven coevolution is able to evolve a broad range of successful team behaviours, which we test on the real multirobot system.
Agradecimentos/Acknowledgements
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Palavras-chave
Cooperative coevolution,Evolutionary robotics,Novelty search,Reality gap,Heterogeneous multirobot systems
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UID/MULTI/04046/2013 Fundação para a Ciência e a Tecnologia
UID/EEA/50008/2013 Fundação para a Ciência e a Tecnologia
SFRH/BD/89095/2012 Fundação para a Ciência e a Tecnologia
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