DocumentCode
233425
Title
Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm
Author
Faelden, Gerard Ely U. ; Maningo, Jose Martin Z. ; Nakano, Reiichiro Christian S. ; Bandala, Argel A. ; Dadios, Elmer P.
Author_Institution
Gokongwei Coll. of Eng., De La Salle Univ., Manila, Philippines
fYear
2014
fDate
12-16 Nov. 2014
Firstpage
1
Lastpage
5
Abstract
There is an increasing research interest in unmanned autonomous vehicles (UAVs) such as quadrotors. These researches applies these quadrotors for much more complicated tasks with most requiring cameras and GPS modules for positioning. This paper presents an alternative way of position localization of a quadrotor without the use of cameras and GPS modules by means of transceivers and Genetic Algorithm (GA). This paper uses the received signals from the transceivers as inputs for the genetic algorithm in order to locate the quadrotor in a xyz axis. Parameters such as location of transceivers, amount of transceivers and population size of the GA are tested in order to determine a successful way of locating the quadrotor. Results show that the different parameters tested were successful and converges to a point usually with a fitness measure greater than 99%. An average fitness measure greater than 99.9900% served as a benchmark for the tests done. The first test achieved this benchmark at about 130 generations and the second test achieved it at 110 generations. The time it took for the program to locate the quadrotor is about 60 milliseconds. Results show that this blind localization technique is successfully locates the quadrotor and may be calibrated to one´s own need.
Keywords
autonomous aerial vehicles; genetic algorithms; GA; GPS modules; UAV; blind localization method; cameras; fitness measure; genetic algorithm; position localization; quadrotor-unmanned aerial vehicle; time 60 ms; transceivers; unmanned autonomous vehicles; Conferences; Genetic algorithms; Global Positioning System; Sociology; Statistics; Testing; Transceivers; UAV; blind localization; genetic algorithm; position; quadrotor; tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), 2014 International Conference on
Conference_Location
Palawan
Print_ISBN
978-1-4799-4021-9
Type
conf
DOI
10.1109/HNICEM.2014.7016214
Filename
7016214
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