Comm_relay_Pawel_Ladosz.pdf (11.16 MB)
Trajectory planning for communication relay unmanned aerial vehicles in urban dynamic environments
journal contribution
posted on 2017-02-06, 15:05 authored by Pawel Ladosz, Hyondong Oh, Wen-Hua ChenWen-Hua ChenThis paper proposes an optimal positioning and trajectory planning algorithm for unmanned aerial vehicles (UAVs) to improve a communication quality of a team of ground mobile nodes (vehicles) in a complex urban environment. In particular, a nonlinear model predictive control (NMPC)-based approach is proposed to find an efficient trajectory for UAVs with a discrete genetic algorithm while considering the dynamic constraints of fixed-wing UAVs. The advantages of using the proposed NMPC approach and the communication performance metrics are investigated through a number of scenarios with different horizon steps in the NMPC framework, the number of UAVs used, heading rates and speeds.
Funding
This work was supported by the UK Engineering and Physical Science Research Council (EPSRC) under the Grant EP/J011525/1 and the Research Fund (Project Number 1.160089) of UNIST (Ulsan National Institute of Science and Technology).
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
Journal of Intelligent & Robotic SystemsCitation
LADOSZ, P., OH, H. and CHEN, W.-H., 2018. Trajectory planning for communication relay unmanned aerial vehicles in urban dynamic environments. Journal of Intelligent & Robotic Systems, 89(1-2), pp. 7-25.Publisher
© SpringerVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2017-01-14Publication date
2017-01-28Notes
This is a post-peer-review, pre-copyedit version of an article published in Journal of Intelligent & Robotic Systems. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10846-017-0484-y.ISSN
0921-0296eISSN
1573-0409Publisher version
Language
- en