Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm
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 o...
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oai:animorepository.dlsu.edu.ph:faculty_research-33402021-08-24T08:02:53Z Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm Faelden, Gerard Ely U. Maningo, Jose Martin Z. Nakano, Reiichiro Christian S. Bandala, Argel A. Dadios, Elmer P. 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. © 2014 IEEE. 2014-01-01T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/2341 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3340/type/native/viewcontent Faculty Research Work Animo Repository Quadrotor helicopters Genetic algorithms Automatic tracking Electrical and Computer Engineering Electrical and Electronics Systems and Communications |
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Quadrotor helicopters Genetic algorithms Automatic tracking Electrical and Computer Engineering Electrical and Electronics Systems and Communications Faelden, Gerard Ely U. Maningo, Jose Martin Z. Nakano, Reiichiro Christian S. Bandala, Argel A. Dadios, Elmer P. Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm |
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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. © 2014 IEEE. |
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Faelden, Gerard Ely U. Maningo, Jose Martin Z. Nakano, Reiichiro Christian S. Bandala, Argel A. Dadios, Elmer P. |
author_facet |
Faelden, Gerard Ely U. Maningo, Jose Martin Z. Nakano, Reiichiro Christian S. Bandala, Argel A. Dadios, Elmer P. |
author_sort |
Faelden, Gerard Ely U. |
title |
Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm |
title_short |
Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm |
title_full |
Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm |
title_fullStr |
Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm |
title_full_unstemmed |
Blind localization method for quadrotor-unmanned aerial vehicle (QUAV) utilizing genetic algortihm |
title_sort |
blind localization method for quadrotor-unmanned aerial vehicle (quav) utilizing genetic algortihm |
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Animo Repository |
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2014 |
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https://animorepository.dlsu.edu.ph/faculty_research/2341 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3340/type/native/viewcontent |
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