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

Alexandros Giagkos, Myra Wilson, Ben Bancroft

Research output: Chapter in Book/Published conference outputConference publication


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-networkaware 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.
Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems (TAROS)
Number of pages10
Publication statusE-pub ahead of print - 8 Sep 2021
EventTowards Autonomous Robotic Systems - Lincoln, Lincoln, United Kingdom
Duration: 8 Sep 202110 Sep 2021
Conference number: 22

Publication series

NameSpringer Lecture Notes in the Artificial Intelligence series


ConferenceTowards Autonomous Robotic Systems
Abbreviated titleTAROS
Country/TerritoryUnited Kingdom
Internet address

Bibliographical note

© 2021 The Authors


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