Subterranean positioning for a semi-autonomous robot supporting emergency task forces

Eva Maria Reitbauer*, Christoph Schmied, Hamid Didari Khamseh Motlagh

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

This paper proposes a positioning algorithm for a semi-autonomous robot in subterranean scenarios. The robot is equipped with positioning sensors, imaging sensors, and sensors to detect hazardous materials. The sensors can be used to automatically generate a site map to increase safety for emergency forces. To create an accurate map, the position and attitude of the robot have to be determined. This is done using an extended Kalman filter which fuses data from LIDAR, wheel odometry, and a MEMS IMU. Tests were carried out in a tunnel in Eisenerz, Austria. To evaluate the achievable accuracy, the estimated position of the filter is compared to a ground truth. The results show that with the developed sensor fusion algorithm, a horizontal positioning error of 1.07% of the traveled distance can be achieved.
Originalspracheenglisch
Titel2022 International Conference on Localization and GNSS (ICL-GNSS)
Redakteure/-innenJari Nurmi, Elena-Simona Lohan, Joaquin Torres Sospedra, Heidi Kuusniemi, Aleksandr Ometov
Herausgeber (Verlag)IEEE Xplore
Seitenumfang7
ISBN (elektronisch)9781665405751
DOIs
PublikationsstatusVeröffentlicht - Juni 2022
Veranstaltung2022 International Conference on Localization and GNSS : ICL-GNSS 2022 - Tampere, Finnland
Dauer: 7 Juni 20229 Juni 2022

Konferenz

Konferenz2022 International Conference on Localization and GNSS
KurztitelICL-GNSS 2022
Land/GebietFinnland
OrtTampere
Zeitraum7/06/229/06/22

ASJC Scopus subject areas

  • Luft- und Raumfahrttechnik
  • Computernetzwerke und -kommunikation

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