Achim Lilienthal, Holger Ulmer, Holger Fröhlich, Andreas Stützle, Felix Werner and Andreas Zell
Gas Source Declaration with a Mobile Robot
ICRA 2004, New Orleans, USA, April 26 - May 1, 2004, pp. 1430 - 1435
Abstract
As a sub-task of the general gas source localisation problem, gas source declaration is the process of determining the certainty that a source is in the immediate vicinity. Due to the turbulent character of gas transport in a natural indoor environment, it is not sufficient to search for instantaneous concentration maxima, in order to solve this task. Therefore, this paper introduces a method to classify whether an object is a gas source or not from a series of concentration measurements, recorded while the robot performs a rotation manoeuvre in front of a possible source. For three different gas source positions, a total of 288 declaration experiments were carried out at different robot-to-source distances. Based on these readings, two machine learning techniques (ANN, SVM) were evaluated in terms of their classification performance. With learning parameters that were optimised by grid search, a maximal hit rate of approximately 87.5% could be obtained using a support vector machine.
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Bibtex
@INPROCEEDINGS{Lilienthal:ICRA2004,
AUTHOR = "Achim J. Lilienthal and Holger Ulmer and Holger Fr{\"o}hlich and Andreas St{\"u}tzle and Felix Werner and Andreas Zell",
TITLE = "Gas Source Declaration with a Mobile Robot",
BOOKTITLE = "Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2004)",
YEAR = "2004",
PAGES = "1430 -- 1435"
}