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Article Details

Article Details

  • Article Code : NWSA-2170-1282
  • Article Type : Araştırma Makalesi
  • Publication Number : 1A0269
  • Page Number : 1630-1644
  • Doi : 10.12739/
  • Abstract Reading : 1306
  • Download : 163
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Issue Details

  • Year : 2011
  • Volume : 6
  • Issue : 4
  • Number of Articles Published : 79
  • Published Date : 1.10.2011

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Dergi Kapağı
Engineering Sciences

Serial Number : 1A
ISSN No. : 1308-7231
Release Interval (in a Year) : 4 Issues

ROBOTİK PROBLEMLERİNİN GA VE PSO İLE ÇÖZÜMÜ İÇİN EĞİTİM AMAÇLI YENİ BİR YAZILIM

METIN TOZ 1 , Pakize ERDOGMUS 2 , Ibrahim ŞAHİN 3

Mobil robotlarda verilen bir i?i yerine etirmek için gerekli yol planlamasynyn yapylmasy ve seri robotlarda ters kinematik hesaplamalar robotik alanyn iki temel problemidir. Bu çaly?mada bu iki problem iki farkly sezgisel optimizasyoN yöntemi olan Genetik Algoritma (GA) ve Parçacyk Sürü Optimizasyonu (PSO) kullanylarak çözülmü?tür. GA ve PSO’dan elde edilen sonuçlar hesaplama yükü ve çözumlerin uygunlu?u açysyndan kar?yla?tyrylmy?tyr. Sonuçlar göstermi?tir ki her iki ka?yla?tyrma kriterine göre de GA yöntemi PSA’ya göre daha iyi sonuç vermi?tir. Bu çaly?mada ayryca GA ve PSO optimizasyon tekniklerinin robotikte kullanymy için e?itim amaçly bir yazylym geli?tirilmi?tir. Yazylym, de?i?ik ortamlarda mobil robot yol planlama problemi ve 6 serbestlik dereceli eklem kaçykly bile?e sahip Puma türü bir robotun ters kinematik probleminin çözümlerinin benzetimini gerçekle?tirecek ?ekilde tasarlanmy?tyr.

Keywords
Mobil Robotlar, Engelden Sakynma, Seri Robotlar, Ters Kinematik, Yol Bulma,

A NEW EDUCATIONAL TOOLBOX FOR SOLVING ROBOTIC OPTIMIZATION PROBLEMS USING GA AND PSO

METIN TOZ 1 , Pakize ERDOGMUS 1 , Ibrahim ŞAHİN 1

Two fundamental problems in robotic are the path planning for mobile robots to achieve a given task and the inverse kinematics for serial robots. In this study, these two problems were solved with two different heuristic optimization methods which are Genetic algorithm (GA) and Particle Swarm Optimization (PSO). GA and PSO results were compared in terms of the computational complexity of the algorithms and the feasibility of the solutions. According to the results, PSO outperforms GA with respect to both comparison criteria. Also, a new toolbox for using these optimization algorithms in robotic was developed for educational purposes. The toolbox was designed to simulate the solution of path planning problem in different environments and the inverse kinematics of a 6 Degrees of Freedom (DOFs) Puma robot with offset wrist.

Keywords
Mobile Robots, Obstacle Avoidance, Serial Robots, Inverse Kinematics, Path Planning,

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Authors

METIN TOZ (1)

metintoz@duzce.edu.tr

Pakize ERDOGMUS (2) (Corresponding Author)
Düzce ÜNİVERSİTESİ
pakizeerdogmus@duzce.edu.tr

Ibrahim ŞAHİN (3)

Düzce ÜNİVERSİTESİ
ibrahimsahin@duzce.edu.tr

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