3D Localization with Conical Vision
Abstract
This paper deals with an absolute mobile robot self-localization algorithm in an indoor environment. Until now, localization methods based on conical omnidirectional vision sensors uniquely used radial segments from vertical environment landmarks projection. The main motivation of this work is to demonstrate that the SYCLOP sensor can be used as a vision sensor rather than a goniometric one. We will show how the calibration allows us to know the omnidirectional image formation process to compute a synthetic image base. Then, we will present the spatial localization method using a base of synthetics images and one real omnidirectional image. Finally, some experimental results obtained with real noisy omnidirectional images are shown.
Cite
Text
Cauchois et al. "3D Localization with Conical Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2003. doi:10.1109/CVPRW.2003.10075Markdown
[Cauchois et al. "3D Localization with Conical Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2003.](https://mlanthology.org/cvprw/2003/cauchois2003cvprw-3d/) doi:10.1109/CVPRW.2003.10075BibTeX
@inproceedings{cauchois2003cvprw-3d,
title = {{3D Localization with Conical Vision}},
author = {Cauchois, Cyril and Brassart, Eric and Delahoche, Laurent and Clerentin, Arnaud},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2003},
pages = {81},
doi = {10.1109/CVPRW.2003.10075},
url = {https://mlanthology.org/cvprw/2003/cauchois2003cvprw-3d/}
}