Vibrational Genetic Algorithm Based Path Planner for Autonomous UAV in Spatial Data Based Environments

Author

Pehlivanoglu, Y. Volkan ; Hacioglu, Abdurrahman

Author_Institution

Air Logistic Command, Ankara

fYear

2007

fDate

14-16 June 2007

Firstpage

573

Lastpage

578

Abstract

Within this study, it is aimed to provide an efficient algorithm for path planning in guidance of autonomous Unmanned Aerial Vehicle (UAV) in spatial data based environments. For this purpose, as a stochastic search method, current vibrational genetic algorithm (VGA) is improved and used to accelerate the algorithm for path planning. From the results obtained, it is concluded that VGA decreased the required time for optimal path solution beside its simplicity. Low population rate and short generation cycle are the main benefits of vibrational genetic algorithm.

Keywords

genetic algorithms; path planning; remotely operated vehicles; stochastic processes; autonomous UAV; autonomous unmanned aerial vehicle; optimal path solution; path planner; path planning; spatial data based environments; stochastic search method; vibrational genetic algorithm; Genetic algorithms; Genetic mutations; Intelligent vehicles; Neural networks; Path planning; Remotely operated vehicles; Skeleton; Space exploration; Stochastic processes; Unmanned aerial vehicles; Path planning; UAV; VGA;

fLanguage

English

Publisher

ieee

Conference_Titel

Recent Advances in Space Technologies, 2007. RAST '07. 3rd International Conference on

Conference_Location

Istanbul

Print_ISBN

1-4244-1057-6

Electronic_ISBN

1-4244-1057-6

Type

conf

DOI

10.1109/RAST.2007.4284058

Filename

4284058