DocumentCode
3136862
Title
Task allocation of multiple UAVs and targets using improved genetic algorithm
Author
Zuo, Yong ; Peng, Zhihong ; Liu, Xin
Author_Institution
Key Lab. of Complex Syst. Intell. Control & Decision, Beijing Inst. of Technol., Beijing, China
Volume
2
fYear
2011
fDate
25-28 July 2011
Firstpage
1030
Lastpage
1034
Abstract
In this paper, task allocation of multi-Unmanned Aerial Vehicles (UAVs) is studied, that is, multi-UAVs from different bases should be allocated to attack multiple targets. Based on the existing task allocation model, which just take the values of targets, UAVs and weapons into account, the fuel consumption is added into consideration to make the model much more practical. An improved genetic algorithm is proposed for such a multi-UAVs multi-targets task allocation. Simulation results show that the algorithm is significantly effective and the allocation result is reasonable.
Keywords
aircraft; genetic algorithms; mobile robots; multi-robot systems; remotely operated vehicles; UAV; fuel consumption; improved genetic algorithm; multitargets task allocation; multiunmanned aerial vehicles; Genetics; Indexes; Navigation; Weapons; Zinc; Genetic Algorithm; Task Allocation; UAV;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4577-0813-8
Type
conf
DOI
10.1109/ICICIP.2011.6008408
Filename
6008408
Link To Document