DocumentCode :
3582809
Title :
Optimization and improvement for multi-UAV cooperative reconnaissance mission planning problem
Author :
Wei-Long Yang ; Luo Lei ; Jing-Sheng Deng
Author_Institution :
Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2014
Firstpage :
10
Lastpage :
15
Abstract :
The Multi-UAV cooperative reconnaissance mission planning is one of the task allocation and resource scheduling problems during the multi-UAV cooperative control. The key to solve this problem is to build a reasonable solving-model and find an effective solving-algorithm. Based on the analysis of characteristics about reconnaissance missions, this paper takes plenty of constraints and performance planning targets in multi-UAV cooperative reconnaissance mission planning problems into full consideration, in particular the number of surveillance for targets, the reconnaissance time, the types of load requirements, and also the performance requirements of UAV, and thus establishes a more practical mathematical model for the multi-base, multi-target, multi-UAV cooperative reconnaissance problem. What is more, for the problems existed when dealing with the model, such as NP-hard and complex constraints, this paper has designed a modified genetic algorithm, based on the classical one, and meanwhile constructed the initial feasible solutions through a heuristic method, which would avoid the over-slow convergence in the process of evolutionary to a large degree.
Keywords :
autonomous aerial vehicles; convergence; cooperative systems; genetic algorithms; multi-robot systems; resource allocation; scheduling; NP-hard; genetic algorithm; load requirement; mathematical model; multiUAV cooperative control; multiUAV cooperative reconnaissance mission planning problem; multibase cooperative reconnaissance; multitarget cooperative reconnaissance; optimization; over-slow convergence; performance planning target; resource scheduling problem; solving-algorithm; target surveillance; task allocation; Biological cells; Genetic algorithms; Heuristic algorithms; Mathematical model; Planning; Reconnaissance; Resource management; Multi-UAV; improved genetic algorithm; initial feasible solutions; mathematical model; mission planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
Print_ISBN :
978-1-4799-7207-4
Type :
conf
DOI :
10.1109/ICCWAMTIP.2014.7073351
Filename :
7073351
Link To Document :
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