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
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;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-0813-8
DOI :
10.1109/ICICIP.2011.6008408