ML Anthology

Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans

Feng Lu, Evangelos E. Milios
CVPR 1994 pp. 935-938
doi:10.1109/CVPR.1994.323928 /cvpr/1994/lu1994cvpr-robot/

Abstract

We develop two algorithms to register a range scan to a previous scan so as to compute relative robot positions in an unknown environment. The first algorithm is used on matching tangent lines defined on two scans and minimizing a distance function. The second algorithm iteratively establishes correspondences between points in the two scans and then solves the point-to-point least-squares problem to compute the relative pose. Our methods avoid the use of localized features. They work in curved environments and can handle partial occlusions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Lu and Milios. "Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994. doi:10.1109/CVPR.1994.323928

Markdown

[Lu and Milios. "Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994.](https://mlanthology.org/cvpr/1994/lu1994cvpr-robot/) doi:10.1109/CVPR.1994.323928

BibTeX

@inproceedings{lu1994cvpr-robot,
  title     = {{Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans}},
  author    = {Lu, Feng and Milios, Evangelos E.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1994},
  pages     = {935-938},
  doi       = {10.1109/CVPR.1994.323928},
  url       = {https://mlanthology.org/cvpr/1994/lu1994cvpr-robot/}
}