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Evaluation of Sensors and Mapping Approaches for Disasters in Tunnels

  • Ground or aerial robots equipped with advanced sensing technologies, such as three-dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state-of-the-art and off-the-shelf components and algorithms are suited for reconnaissance in current disaster-relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster-relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state-of-the-art and off-the-shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search.

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Metadaten
Verfasserangaben:Max Leingartner, Johannes Maurer, Alexander FerreinORCiD, Gerald Steinbauer
DOI:https://doi.org/10.1002/rob.21611
ISSN:1556-4967
Titel des übergeordneten Werkes (Englisch):Journal of Field Robotics
Verlag:Wiley-VCH
Verlagsort:Weinheim
Dokumentart:Wissenschaftlicher Artikel
Sprache:Englisch
Erscheinungsjahr:2016
Datum der Publikation (Server):01.02.2016
Jahrgang:33
Ausgabe / Heft:8
Erste Seite:1037
Letzte Seite:1057
Link:https://doi.org/10.1002/rob.21611
Zugriffsart:campus
Fachbereiche und Einrichtungen:FH Aachen / Fachbereich Elektrotechnik und Informationstechnik
FH Aachen / MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik
collections:Verlag / Wiley-VCH