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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. R., López-Ibáñez, M., Ochoa, G., and Paechter, B. (Ed.), Parallel Problem Solving from Nature – PPSN XIV. Lecture Notes in Computer Science. (pp. 591-601). Edinburgh: Springer.

J. Gomes et al.,  "Cooperative coevolution of control for a real multirobot system", in Parallel Problem Solving from Nature – PPSN XIV. Lecture Notes in Computer Science, Handl, J., Hart, E., Lewis, P. R., López-Ibáñez, M., Ochoa, G., and Paechter, B., Ed., Edinburgh, Springer, 2016, vol. 9921, pp. 591-601

@inproceedings{gomes2016_1733338106423,
	author = "Gomes, J. and Duarte, M. and Mariano, P. and Christensen, A. L.",
	title = "Cooperative coevolution of control for a real multirobot system",
	booktitle = "Parallel Problem Solving from Nature – PPSN XIV. Lecture Notes in Computer Science",
	year = "2016",
	editor = "Handl, J., Hart, E., Lewis, P. R., López-Ibáñez, M., Ochoa, G., and Paechter, B.",
	volume = "9921",
	number = "",
	series = "",
	doi = "10.1007/978-3-319-45823-6_55",
	pages = "591-601",
	publisher = "Springer",
	address = "Edinburgh",
	organization = "Edinburgh Napier University",
	url = "https://link.springer.com/book/10.1007/978-3-319-45823-6"
}

TY  - CPAPER
TI  - Cooperative coevolution of control for a real multirobot system
T2  - Parallel Problem Solving from Nature – PPSN XIV. Lecture Notes in Computer Science
VL  - 9921
AU  - Gomes, J.
AU  - Duarte, M.
AU  - Mariano, P.
AU  - Christensen, A. L.
PY  - 2016
SP  - 591-601
DO  - 10.1007/978-3-319-45823-6_55
CY  - Edinburgh
UR  - https://link.springer.com/book/10.1007/978-3-319-45823-6
AB  - 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.
ER  -