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Approaches to Time-Dependent Gas Distribution Modelling
Örebro University, School of Science and Technology. (AASS)
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-0217-9326
2015 (English)In: 2015 European Conference on Mobile Robots (ECMR), New York: IEEE conference proceedings , 2015, 7324215Conference paper, Published paper (Refereed)
Abstract [en]

Mobile robot olfaction solutions for gas distribution modelling offer a number of advantages, among them autonomous monitoring in different environments, mobility to select sampling locations, and ability to cooperate with other systems. However, most data-driven, statistical gas distribution modelling approaches assume that the gas distribution is generated by a time-invariant random process. Such time-invariant approaches cannot model well developing plumes or fundamental changes in the gas distribution. In this paper, we discuss approaches that explicitly consider the measurement time, either by sub-sampling according to a given time-scale or by introducing a recency weight that relates measurement and prediction time. We evaluate the performance of these time-dependent approaches in simulation and in real-world experiments using mobile robots. The results demonstrate that in dynamic scenarios improved gas distribution models can be obtained with time-dependent approaches.

Place, publisher, year, edition, pages
New York: IEEE conference proceedings , 2015. 7324215
Keyword [en]
Dispersion; Kernel; Pollution measurement; Predictive models; Robot sensing systems; Time measurement; Weight measurement
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-51939DOI: 10.1109/ECMR.2015.7324215ISI: 000380213600049Scopus ID: 2-s2.0-84962271801ISBN: 978-1-4673-9163-4 (print)OAI: oai:DiVA.org:oru-51939DiVA: diva2:957520
Conference
European Conference on Mobile Robots, Lincoln, England, September 2-4, 2015
Available from: 2016-09-02 Created: 2016-09-02 Last updated: 2017-10-18Bibliographically approved

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Asadi, SaharLilienthal, Achim

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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Output format
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  • asciidoc
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