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Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms
BAM Federal Institute for Materials Research and Testing, Berlin, Germany. (AASS MRO Lab)
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0001-5061-5474
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-0217-9326
BAM Federal Institute for Materials Research and Testing, Berlin, Germany.
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2013 (English)In: Advanced Robotics, ISSN 0169-1864, E-ISSN 1568-5535, ISSN 0169-1864, Vol. 27, no 9, 725-738 p.Article in journal (Refereed) Published
Abstract [en]

Gas source localization (GSL) with mobile robots is a challenging task due to the unpredictable nature of gas dispersion,the limitations of the currents sensing technologies, and the mobility constraints of ground-based robots. This work proposesan integral solution for the GSL task, including source declaration. We present a novel pseudo-gradient-basedplume tracking algorithm and a particle filter-based source declaration approach, and apply it on a gas-sensitivemicro-drone. We compare the performance of the proposed system in simulations and real-world experiments againsttwo commonly used tracking algorithms adapted for aerial exploration missions.

Place, publisher, year, edition, pages
2013. Vol. 27, no 9, 725-738 p.
Keyword [en]
autonomous micro UAV; chemical and wind sensing; gas source localization; particle filter
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-30542DOI: 10.1080/01691864.2013.779052ISI: 000318869000007Scopus ID: 2-s2.0-84877939308OAI: oai:DiVA.org:oru-30542DiVA: diva2:644489
Projects
Gasbot (Robotdalen, project number 8140)
Available from: 2013-08-30 Created: 2013-08-30 Last updated: 2017-12-06Bibliographically approved

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Hernandez Bennetts, VictorLilienthal, Achim J.

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