Pipeline Landmark Detection for Autonomous Robot Navigation Using Time-of-Flight Imagery
Abstract
3D imaging systems provide valuable information for autonomous robot navigation based on landmark detection in pipelines. This paper presents a method for using a time-of-flight (TOF) camera for detection and tracking of pipeline features such as junctions, bends and obstacles. Feature extraction is done by fitting a cylinder to images of the pipeline. Data in captured images appear to take a conic rather than cylindrical shape, and we adjust the geometric primitive accordingly. Pixels deviating from the estimated cylinder/cone fit are grouped into blobs. Blobs fulfilling constraints on shape and stability over time are then tracked. The usefulness of TOF imagery as a source for landmark detection and tracking in pipelines is evaluated by comparison to auxiliary measurements. Experiments using a model pipeline and a prototype robot show encouraging results.
Cite
Text
Thielemann et al. "Pipeline Landmark Detection for Autonomous Robot Navigation Using Time-of-Flight Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563167Markdown
[Thielemann et al. "Pipeline Landmark Detection for Autonomous Robot Navigation Using Time-of-Flight Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/thielemann2008cvprw-pipeline/) doi:10.1109/CVPRW.2008.4563167BibTeX
@inproceedings{thielemann2008cvprw-pipeline,
title = {{Pipeline Landmark Detection for Autonomous Robot Navigation Using Time-of-Flight Imagery}},
author = {Thielemann, Jens T. and Breivik, Gøril M. and Berge, Asbjørn},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2008},
pages = {1-7},
doi = {10.1109/CVPRW.2008.4563167},
url = {https://mlanthology.org/cvprw/2008/thielemann2008cvprw-pipeline/}
}