Experimental validation of domain knowledge assisted robotic exploration and source localization

Thomas Wiedemann, Dmitriy Shutin, Achim J. Lilienthal

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

7 Zitate (Scopus)

Abstract

In situations where toxic or dangerous airborne material is leaking, mobile robots equipped with gas sensors are a safe alternative to human reconnaissance. This work presents the Domain Knowledge Assisted Robotic Exploration and Source Localization (DARES) approach. It allows a multi-robot system to localize multiple sources or leaks autonomously and independently of a human operator. The probabilistic approach builds upon domain knowledge in the form of a physical model of gas dispersion and the a priori assumption that the dispersion process is driven by multiple but sparsely distributed sources. A formal criterion is used to guide the robots to informative measurement locations and enables inference of the source distribution based on gas concentration measurements. Small-scale indoor experiments under controlled conditions are presented to validate the approach. In all three experiments, three rovers successfully localized two ethanol sources.

OriginalspracheEnglisch
TitelICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9781728172897
DOIs
PublikationsstatusVeröffentlicht - 11 Aug. 2021
Extern publiziertJa
Veranstaltung2021 IEEE International Conference on Autonomous Systems, ICAS 2021 - Virtual, Montreal, Kanada
Dauer: 11 Aug. 202113 Aug. 2021

Publikationsreihe

NameICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings

Konferenz

Konferenz2021 IEEE International Conference on Autonomous Systems, ICAS 2021
Land/GebietKanada
OrtVirtual, Montreal
Zeitraum11/08/2113/08/21

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