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Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

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2083-2567
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Simulation and Experimental Evaluation of the EKF Simultaneous Localization and Mapping Algorithm on the Wifibot Mobile Robot

Noura Ayadi / Nabil Derbel / Nicolas Morette / Cyril Novales / Gérard Poisson
Published Online: 2017-11-01 | DOI: https://doi.org/10.1515/jaiscr-2018-0006

Abstract

In recent years, autonomous navigation for mobile robots has been considered a highly active research field. Within this context, we are interested to apply the Simultaneous Localization And Mapping (SLAM) approach for a wheeled mobile robot. The Extended Kalman Filter has been chosen to perform the SLAM algorithm. In this work, we explicit all steps of the approach. Performances of the developed algorithm have been assessed through simulation in the case of a small scale map. Then, we present several experiments on a real robot that are proceeded in order to exploit a programmed SLAM unit and to generate the navigation map. Based on experimental results, simulation of the SLAM method in the case of a large scale map is then realized. Obtained results are exploited in order to evaluate and compare the algorithm’s consistency and robustness for both cases.

Keywords: mobile robot; localisation; EKF; SLAM; consistency

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About the article

Received: 2017-01-24

Accepted: 2017-03-24

Published Online: 2017-11-01

Published in Print: 2018-04-01


Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 8, Issue 2, Pages 91–101, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2018-0006.

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© 2018 Noura Ayadi et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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