Seyyar Robotlarda Kullanılan Stokastik Konum Belirleme Algoritmalarının Karşılaştırmalı Analizi
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 fundamenta...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Kyrgyz Turkish Manas University
2015-05-01
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| Series: | MANAS: Journal of Engineering |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/en/download/article-file/575943 |
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| Summary: | 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. |
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| ISSN: | 1694-7398 |