Stammdaten

Titel: Artificial Landmarks for Trusted Localization of Autonomous Vehicles Based on Magnetic Sensors
Untertitel:
Kurzfassung:

Magnetic sensors provide an advantageous alternative localization method, primarily focusing on localization in surroundings where GPS, other radio frequency-based, as well as optical localization do not work or has severe limitations. Suitable for distances in the meter range, such magnetic localization may in particular be useful as artificial landmarks, e.g., for automatic drift correction. To easily use such artificial landmarks, we propose an integration process based on Transducer Electronic Data Sheets. With this approach, the landmarks can be used by passing autonomous vehicles, e.g., UAVs, for re-orientation and re-calibration. During this process, all necessary information such as data formats, reference coordinates, calibration data, provider of the landmark etc. is made known to the vehicle passing by. Based on the provided so-called meta-information, the vehicle itself can decide whether and how to use the provided sensory information. To provide a certain level of trust in the landmarks and their provided information, the corresponding data sheets are certified using a digital signature.

Schlagworte: wireless sensor network; magnetic sensor; sensor calibration; sensor authentication
Publikationstyp: Beitrag in Zeitschrift (Autorenschaft)
Art der Veröffentlichung Online Publikation
Erschienen in: Sensors
Sensors
zur Publikation
 ( MDPI Publishing; )
Erscheinungsdatum: 16.02.2019
Titel der Serie: Eurosensors 2018 Selected Papers
Bandnummer: 19
Heftnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 1 - 10

Identifikatoren

ISBN: -
ISSN: 1424-8220
DOI: http://dx.doi.org/10.3390/s19040813
AC-Nummer: -
Homepage: https://www.mdpi.com/1424-8220/19/4/813
Open Access
  • Online verfügbar (Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Intelligente Systemtechnologien
Universitätsstraße 65-67
9020 Klagenfurt am Wörthersee
Österreich
   stephan.weiss@aau.at
http://www.uni-klu.ac.at/tewi/ict/sst/index.html
zur Organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 202036 - Sensorik
Forschungscluster
  • Selbstorganisierende Systeme
Zitationsindex
  • Science Citation Index Expanded (SCI Expanded)
Informationen zum Zitationsindex: Master Journal List
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: I)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Sensor- und Aktortechnik

Kooperationen

Keine Partnerorganisation ausgewählt

Beiträge der Publikation

Keine verknüpften Publikationen vorhanden