To be able to operate and act successfully, the robot needs to know at any time where it is. This means the robot has to find out its location relative to the environment. This contribution introduces the increase of accuracy of mobile robot positioning in large outdoor environments based on data fusion from different sensors: camera, GPS, inertial navigation system (INS), and wheelencoders. The fusion is done in a Simultaneous Localization and Mapping (SLAM) approach.
Berrabah, SA, Baudoin, Y & Sahli, H 2010, 'Multi-Sensor SLAM Approach for Robot Navigation', Sensors & Transducers Journal, vol. 9, pp. 200-213.
Berrabah, SA., Baudoin, Y., & Sahli, H. (2010). Multi-Sensor SLAM Approach for Robot Navigation. Sensors & Transducers Journal, 9, 200-213.
@article{286e3d1dd13e4636b525a44197035a1f,
title = "Multi-Sensor SLAM Approach for Robot Navigation",
abstract = "To be able to operate and act successfully, the robot needs to know at any time where it is. This means the robot has to find out its location relative to the environment. This contribution introduces the increase of accuracy of mobile robot positioning in large outdoor environments based on data fusion from different sensors: camera, GPS, inertial navigation system (INS), and wheelencoders. The fusion is done in a Simultaneous Localization and Mapping (SLAM) approach.",
keywords = "robot navigation, Visual SLAM, GPS",
author = "Sid'Ahmed Berrabah and Yvan Baudoin and Hichem Sahli",
year = "2010",
language = "English",
volume = "9",
pages = "200--213",
journal = "Sensors & Transducers Journal",
issn = "2306-8515",
publisher = "International Frequency Sensor Association (IFSA)",
}