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Network-Aware Genetic Algorithms for the Coordination of MALE UAV Networks

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Towards Autonomous Robotic Systems (TAROS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13054))

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Abstract

Maintaining an ad hoc network infrastructure to cover multiple ground-based users can be achieved by autonomous groups of hydrocarbon powered medium-altitude, long-endurance (MALE) unmanned aerial vehicles (UAVs). This can be seen as an optimisation problem to maximise the number of users supported by a quality network while making efficient use of the available power. We present an architecture that combines genetic algorithms with a network simulator to evolve flying solutions for groups of UAVs. Results indicate that our system generates physical network topologies that are usable and offer consistent network quality. It offers a higher goodput than the non-network-aware equivalent when covering the communication demands of multiple ground-based users. Most importantly, the proposed architecture flies the UAVs at lower altitudes making sure that downstream links remain active throughout the duration of the mission.

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Notes

  1. 1.

    While the GAs search for solutions, the default UAV manoeuvre is to cruise in circles.

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Correspondence to Alexandros Giagkos .

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Giagkos, A., Wilson, M.S., Bancroft, B. (2021). Network-Aware Genetic Algorithms for the Coordination of MALE UAV Networks. In: Fox, C., Gao, J., Ghalamzan Esfahani, A., Saaj, M., Hanheide, M., Parsons, S. (eds) Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science(), vol 13054. Springer, Cham. https://doi.org/10.1007/978-3-030-89177-0_12

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  • DOI: https://doi.org/10.1007/978-3-030-89177-0_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89176-3

  • Online ISBN: 978-3-030-89177-0

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