Seyyar Robotlarda Kullanılan Stokastik Konum Belirleme Algoritmalarının Karşılaştırmalı Analizi

Year 2015, Volume: 3 Issue: 1, 21 - 34, 01.05.2015

U. Bayaliev U. Brimkulov R. Sultanov

Abstract

The problem of mobile robot localization is the problem of finding robots position in its environment. Localization ability plays important role for mobile and autonomous robots because robot must know its position to reach the goal. There are several types of localization problem. The fundamental one is | Position tracking | . In this case the initial position of the robot is known and the problem is at correcting its position after moving some steps is | Position tracking | . Global localization is harder because in this problem the robots initial position is not known and the movement and sensing of the robot may be erroneous. In this case robot must use the movement and sensor information to generate some belief about its position and solve the problem using stochastic methods. This study analyzes and compares stochastic algorithms for solving robot localization problem. To achive this, visual applications for Markov, Kalman and Monte-Carlo algorithms are implemented and their validity in solving the robot localization problem is shown.

Keywords

Mobile Robot, Localization, Markov, Kalman, Monte-Carlo, Algorithm, Stochastic methods

Seyyar Robotlarda Kullanılan Stokastik Konum Belirleme Algoritmalarının Karşılaştırmalı Analizi

Abstract

Seyyar robotların konum belirleme problemi robotun ortamdaki kendi konumunu bulmaya yönelik çalışmasıdır. Konum belirleme kabiliyeti seyyar ve otonom robotlar için önemli rol oynar çünkü robot amacına ulaşmak için konumunu bilmesi gerekir. Konum belirleme probleminin birkaç türü vardır. En temel problem 'Konum takip etme'dir. Bu durumda robotun başlangıç konumu bilinmektedir ve bir kaç hareket sonrasında robotun konumunu doğrulamaya 'Konum takip etme' denir. Global konum belirleme ise daha zordur, çünkü bu problemde robotun başlangıçtaki konumu bilinmemektedir ve ayrıca robotun hareket ve sensörlerinde hata olabilir. Bu durumda robot sensör ve hareket bilgilerini kullanarak konumu hakkında farklı tahmin ve ınanç oluşturduktan sonra problemi stokastik yöntemler ile çözmesi gerekir. Bu çalışmada robotun konum belirleme problemini çözen stokastik algoritmalar incelenip birbiri ile karşılaştırılmaktadır. Bunu yapmak için Markov, Kalman ve Monte-Carlo algoritmalar için görsel uygulama yapılarak problemi çözmedeki geçerliliği gösterilmektedir

Keywords

Seyyar Robot, Konum belirleme, Markov, Kalman, Monte-Carlo, Stokastik yöntemler

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