Application of semantic segmentation for an autonomous rail tamping assistance system

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

Research output: Chapter in Book/Report/Conference proceedingsConference contribution

1 Citation (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.

Original languageEnglish
Title of host publicationIS&T Electronic Imaging 2019
Volume2019
Edition7
DOIs
Publication statusPublished - 13 Jan 2019
EventIntelligent Robotics and Industrial Applications using Computer Vision 2019 - San Francisco, United States
Duration: 13 Jan 201917 Jan 2019
https://www.imaging.org/site/IST/Conferences/EI/EI_2019/Conference/C_IRIACV.aspx

Publication series

NameIS and T International Symposium on Electronic Imaging Science and Technology

Conference

ConferenceIntelligent Robotics and Industrial Applications using Computer Vision 2019
CountryUnited States
CitySan Francisco
Period13.01.201917.01.2019
Internet address

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