Sektörel grid temelli mihverleme yöntemi ve genetik algoritmalarla insansız kara aracı navigasyonu

Bu çalışmada, bilinmeyen bir çevrede hareket eden İnsansız Kara Aracı’nın otonom navigasyonu Genetik Algoritmalar kullanılarak, Sektörel Grid Temelli Mihverleme Yöntemi’yle gerçeklenmiştir. Algoritma için üç boyutlu çevre iki boyutlu sayısal bir matrise indirgenmiş ve arazi yapısı ile engeller matrise birebir yansıtılmıştır. Hata oranları da dahil gerçek algılama girdileri ile lokalizasyon verilerinin matrise entegre edilebilmesi için modüler bir kod yapısı hakim kılınmıştır. Matematiksel altyapı Kartezyen Koordinat Sistemi’ne oturtularak işlem basitliği ön plana çıkarılmıştır. Simülasyonlar bilgisayar ortamında yoğun engelli ve aşırı bozuk arazilerde gerçeklenerek algoritmanın çalışırlığı test edilmiştir

Unmanned ground vehicle navigation with sectoral grid based axising method and genetic algorithms

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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