Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

Optimal application of unmanned aerial vehicle in disaster relief

Authors
Tianying Xie, Yantao Li
Corresponding Author
Tianying Xie
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.30How to use a DOI?
Keywords
UAV, Collaborative Planning, Genetic Algorithm, Nonlinear Optimization Model,
Abstract
Based on the theory of optimization, this paper researches the route planning of multi unmanned aerial vehicle(UAV) cooperative task and the task planning problem of multi UAV scheduling. In this paper, we set up a feature point location model based on the traditional base station location model, which is our basic model. The problem one researches the task planning of UAV cooperative investigation. We transform the problem into the multiple traveling salesman problem and use genetic algorithm to get the optimal number and route of UAV with high computational efficiency. The optimization model is also established, and the genetic algorithm is used to solve it, so as to calculate the optimal number and route of UAV and the flight time of each UAV. Problem two researches the multi-starting multi-unmanned aerial vehicle cooperative investigation task planning problem. Problem three researches the scheduling problem of UAV with communication constraints.
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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.30How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Tianying Xie
AU  - Yantao Li
PY  - 2018/05
DA  - 2018/05
TI  - Optimal application of unmanned aerial vehicle in disaster relief
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SP  - 171
EP  - 175
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.30
DO  - https://doi.org/10.2991/amcce-18.2018.30
ID  - Xie2018/05
ER  -