Evolutionary coordination system for fixed-wing communications unmanned aerial vehicles

Giagkos, Alexandros and Tuci, Elio and Wilson, Myra S. and Charlesworth, Philip B. (2014) Evolutionary coordination system for fixed-wing communications unmanned aerial vehicles. In: TAROS 2014: 15th Towards Autonomous Robotic Systems annual conference, 01-03 Sept 2014, Birmingham, United Kingdom.

[img]
Preview
PDF - Final accepted version (with author's formatting)
Download (1MB) | Preview

Abstract

A system to coordinate the movement of a group of un- manned aerial vehicles that provide a network backbone over mobile ground-based vehicles with communication needs is presented. Using evo- lutionary algorithms, the system evolves flying manoeuvres that position the aerial vehicles by fulfilling two key requirements; i) they maximise net coverage and ii) they minimise the power consumption. Experimental results show that the proposed coordination system is able to offer a de- sirable level of adaptability with respect to the objectives set, providing useful feedback for future research directions.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as: Giagkos A., Tuci E., Wilson M.S., Charlesworth P.B. (2014) Evolutionary Coordination System for Fixed-Wing Communications Unmanned Aerial Vehicles. In: Mistry M., Leonardis A., Witkowski M., Melhuish C. (eds) Advances in Autonomous Robotics Systems. TAROS 2014. Lecture Notes in Computer Science, vol 8717. Springer, Cham
Research Areas: A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 21945
Notes on copyright: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-10401-0_5
Depositing User: Elio Tuci
Date Deposited: 07 Jun 2017 14:10
Last Modified: 09 Nov 2018 06:27
URI: http://eprints.mdx.ac.uk/id/eprint/21945

Actions (login required)

Edit Item Edit Item

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year