Probabilistic Approach to Mobile Robot Localization Based on Gaussian Models of Sensors
In this paper the probabilistic approach to mobile robot localization is discussed. Generally probabilistic localization uses some type of sensors model. In this paper Gaussian model, which is the most appropriate probabilistic model of the sensors, is used. The main body of the article deal with th...
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| Veröffentlicht in: | Applied Mechanics and Materials 2014-07, Vol.607 (Machine Design and Manufacturing Engineering III), p.803-810 |
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| container_issue | Machine Design and Manufacturing Engineering III |
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| container_title | Applied Mechanics and Materials |
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| creator | Hubinský, Peter Duchoň, František Babinec, Andrej Fico, Tomas Rodina, Jozef |
| description | In this paper the probabilistic approach to mobile robot localization is discussed. Generally probabilistic localization uses some type of sensors model. In this paper Gaussian model, which is the most appropriate probabilistic model of the sensors, is used. The main body of the article deal with the proposal of own approach to probabilistic localization, which is inspired by Markov localization. That is why the Markov localization is described in the introduction of the article. At the end of the article several experiments with the real robot are described. Results of the experiments have proven that proposed localization is accurate, fast and reliable. |
| doi_str_mv | 10.4028/www.scientific.net/AMM.607.803 |
| format | Article |
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| subjects | Gaussian Localization Markov processes Position (location) Probabilistic methods Probability theory Robots Sensors |
| title | Probabilistic Approach to Mobile Robot Localization Based on Gaussian Models of Sensors |
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