Application of semantic segmentation for an autonomous rail tamping assistance system

Gerald Zauner, Tobias Müller, Andreas Theiß, Martin Bürger, Florian Auer

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitrag

1 Zitat (Scopus)

Abstract

Safe and comfortable travel on the train is only possible on tracks that are in the correct geometric position. For this reason, track tamping machines are used worldwide that carry out this important track maintenance task. Turnout-ta.mping refers to a complex procedure for the improvement and stabilization of the track situation in turnouts, which is carried out usually by experienced operators. This application paper describes the current state of development of a 3D laser line scanner-based sensor system for a new turnout-tamping assistance system, which is able to support and relieve the operator in complex tamping areas. A central task in this context is digital image processing, which carries out so-called semantic segmentation (based on deep learning algorithms) on the basis of 3D scanner data in order to detect essential and critical rail areas fully automatically.

OriginalspracheEnglisch
TitelIS&T Electronic Imaging 2019
Band2019
Auflage7
DOIs
PublikationsstatusVeröffentlicht - 13 Jän 2019
VeranstaltungIntelligent Robotics and Industrial Applications using Computer Vision 2019 - San Francisco, USA/Vereinigte Staaten
Dauer: 13 Jän 201917 Jän 2019
https://www.imaging.org/site/IST/Conferences/EI/EI_2019/Conference/C_IRIACV.aspx

Publikationsreihe

NameIS and T International Symposium on Electronic Imaging Science and Technology

Konferenz

KonferenzIntelligent Robotics and Industrial Applications using Computer Vision 2019
Land/GebietUSA/Vereinigte Staaten
OrtSan Francisco
Zeitraum13.01.201917.01.2019
Internetadresse

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