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

  • Rafet Aksoy
  • Sefer Kurnaz
Keywords: Robot, Unmanned Ground Vehicles, Genetic Algorithms, Autonomy, Navigation, Path Planning

Abstract

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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Published
2009-01-26
How to Cite
[1]
R. Aksoy and S. Kurnaz, “SEKTÖREL GRİD TEMELLİ MİHVERLEME YÖNTEMİ VE GENETİK ALGORİTMALARLA İNSANSIZ KARA ARACI NAVİGASYONU”, JAST, vol. 4, no. 1, pp. 33-45, Jan. 2009.
Section
Articles