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Cooperative Coevolution of Control for a Real Multirobot System

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Parallel Problem Solving from Nature – PPSN XIV (PPSN 2016)

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Abstract

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.

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Notes

  1. 1.

    https://github.com/BioMachinesLab/drones/tree/master/JBotAquatic.

  2. 2.

    Videos and logs of the experiments: http://dx.doi.org/10.5281/zenodo.49582.

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Acknowledgements

This work was supported by centre grant (to BioISI, Centre Reference: UID/MULTI/04046/2013), from FCT/MCTES/PIDDAC, Portugal, and by grants SFRH/BD/89095/2012 and UID/EEA/50008/2013.

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Correspondence to Jorge Gomes .

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Gomes, J., Duarte, M., Mariano, P., Christensen, A.L. (2016). Cooperative Coevolution of Control for a Real Multirobot System. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_55

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  • DOI: https://doi.org/10.1007/978-3-319-45823-6_55

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