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

Alexandros Giagkos*, Myra S. Wilson, Ben Bancroft

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)


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.

Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems - 22nd Annual Conference, TAROS 2021, Proceedings
EditorsCharles Fox, Junfeng Gao, Amir Ghalamzan Esfahani, Mini Saaj, Marc Hanheide, Simon Parsons
PublisherSpringer Nature
Number of pages10
ISBN (Electronic)9783030891770
ISBN (Print)9783030891763
Publication statusPublished - 31 Oct 2021
Event22th Annual Conference Towards Autonomous Robotic Systems, TAROS 2021 - Virtual, Online
Duration: 08 Sept 202110 Sept 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13054 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22th Annual Conference Towards Autonomous Robotic Systems, TAROS 2021
CityVirtual, Online
Period08 Sept 202110 Sept 2021


  • Genetic algorithms
  • Networks
  • Unmanned aerial vehicles
  • Wireless communication


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