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Gas source declaration with a mobile robot
University of Tübingen, Tübingen, Germany. (Learning Systems Lab)ORCID iD: 0000-0003-0217-9326
University of Tübingen, Tübingen, Germany. (WSI)
University of Tübingen, Tübingen, Germany. (WSI)
University of Tübingen, Tübingen, Germany. (WSI)
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2004 (English)In: 2004 IEEE International Conference on Robotics and Automation, New York, USA: IEEE, 2004, p. 1430-1435Conference paper, Published paper (Refereed)
Abstract [en]

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

Place, publisher, year, edition, pages
New York, USA: IEEE, 2004. p. 1430-1435
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-4000DOI: 10.1109/ROBOT.2004.1308025PubMedID: 000221794800231Scopus ID: 2-s2.0-3042631887ISBN: 0-7803-8232-3 (print)OAI: oai:DiVA.org:oru-4000DiVA, id: diva2:138299
Conference
2004 IEEE international conference on robotics and automation, ICRA '04, April 26-May 1, 2004
Available from: 2007-09-03 Created: 2007-09-03 Last updated: 2018-04-24Bibliographically approved

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Gas Source Declaration with a Mobile Robot(470 kB)43 downloads
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Lilienthal, Achim J.

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