Route Planning of UAV Based on Improved Ant Colony Algorithm

DOI

10.2991/lemcs-15.2015.283How to use a DOI?

Keywords

UAV; Ant Colony Algorithm; Route Planning; Dual population; GA Algorithm

Abstract

On the basis of analyzing the tactical characteristics and the mission requirements of UAV, a route planning model is established, which is composed of a comprehensive threat model, a performance constraint model and a mission effectiveness model. A dual population genetic ant colony algorithm is designed, with which dual population ant colony can be searched and iterated independently at same time. In the iterative process, bi-directional dynamic adjust adaptively the volatile coefficient of the pheromone which is limited within a certain range. This algorithm can avoid local optimum and stagnation in the search and iteration. Finally The improved ant colony algorithm is applied to the route planning of UAV, and the feasibility and effectiveness of this method is verified by simulation.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhengxiang Qian
AU  - Guocheng Wang
AU  - Jingen Wang
AU  - Yongxin Shi
PY  - 2015/07
DA  - 2015/07
TI  - Route Planning of UAV Based on Improved Ant Colony Algorithm
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 1421
EP  - 1426
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.283
DO  - 10.2991/lemcs-15.2015.283
ID  - Qian2015/07
ER  -