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Bringing Mobile Robot Olfaction to the Next Dimension - UAV-based Remote Sensing of Gas Clouds and Source Localization
Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany. (BAM, Berlin)
Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany. (BAM, Berlin)
Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany. (BAM, Berlin)
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-0217-9326
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2017 (English)In: 2017 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 3910-3916Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we introduce and present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing the gas sensing and aiming capabilities under realistic conditions.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 3910-3916
Series
IEEE International Conference on Robotics and Automation, ISSN 1050-4729
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-64767DOI: 10.1109/ICRA.2017.7989450Scopus ID: 2-s2.0-85027982828ISBN: 978-1-5090-4633-1 (electronic)ISBN: 978-1-5090-4634-8 (print)OAI: oai:DiVA.org:oru-64767DiVA, id: diva2:1179677
Conference
2017 IEEE International Conference on Robotics and Automation (ICRA 2017), Singapore, May 29 - June 3, 2017
Available from: 2018-02-01 Created: 2018-02-01 Last updated: 2019-03-04Bibliographically approved

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Hüllmann, DinoLilienthal, Achim

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