SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU

In this study, autonomous navigation of an Unmanned Ground Vehicle moving in an unknown environment is realized with Genetic Algorithms using Sectoral Grid Based Axising Method. For the algorithm, three dimensional environment is reduced to two dimensional numerical matrix. Terrain structure as we...

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Main Authors: Rafet Aksoy, Sefer Kurnaz
Format: Article
Language:English
Published: Turkish Air Force Academy 2009-01-01
Series:Havacılık ve Uzay Teknolojileri Dergisi
Subjects:
Online Access:http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/198/186
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author Rafet Aksoy
Sefer Kurnaz
author_facet Rafet Aksoy
Sefer Kurnaz
author_sort Rafet Aksoy
collection DOAJ
description In this study, autonomous navigation of an Unmanned Ground Vehicle moving in an unknown environment is realized with Genetic Algorithms using Sectoral Grid Based Axising Method. For the algorithm, three dimensional environment is reduced to two dimensional numerical matrix. Terrain structure as well as obstacles are mapped one to oneon to the matrix. Coding is based upon modularity for integrating real sensing and localization inputs into the matrix including error rates. Mathematical formulization is build over Cartesian Coordinate System for computational simplicity. Simulations are made in intense obstacle and severe terrain conditions. The algorithm’s performance is tested and the results are discussed.
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spelling doaj.art-73e051d49b9e4ca8846cb4c80cded0b52023-02-15T16:20:21ZengTurkish Air Force AcademyHavacılık ve Uzay Teknolojileri Dergisi1304-04481304-04482009-01-01413345SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONURafet Aksoy 0Sefer Kurnaz1Turkish Air Force AcademyTurkish Air Force AcademyIn this study, autonomous navigation of an Unmanned Ground Vehicle moving in an unknown environment is realized with Genetic Algorithms using Sectoral Grid Based Axising Method. For the algorithm, three dimensional environment is reduced to two dimensional numerical matrix. Terrain structure as well as obstacles are mapped one to oneon to the matrix. Coding is based upon modularity for integrating real sensing and localization inputs into the matrix including error rates. Mathematical formulization is build over Cartesian Coordinate System for computational simplicity. Simulations are made in intense obstacle and severe terrain conditions. The algorithm’s performance is tested and the results are discussed.http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/198/186RobotUnmanned Ground VehiclesGenetic AlgorithmsAutonomyNavigationPath Planning
spellingShingle Rafet Aksoy
Sefer Kurnaz
SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU
Havacılık ve Uzay Teknolojileri Dergisi
Robot
Unmanned Ground Vehicles
Genetic Algorithms
Autonomy
Navigation
Path Planning
title SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU
title_full SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU
title_fullStr SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU
title_full_unstemmed SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU
title_short SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU
title_sort sektorel grid temelli mihverleme yontemi ve genetik algoritmalarla insansiz kara araci navigasyonu
topic Robot
Unmanned Ground Vehicles
Genetic Algorithms
Autonomy
Navigation
Path Planning
url http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/198/186
work_keys_str_mv AT rafetaksoy sektorelgridtemellimihverlemeyontemivegenetikalgoritmalarlainsansizkaraaracinavigasyonu
AT seferkurnaz sektorelgridtemellimihverlemeyontemivegenetikalgoritmalarlainsansizkaraaracinavigasyonu