ML Anthology

Optimal Robot Self-Localization and Reliability Evaluation

Ken-ichi Kanatani, Naoya Ohta
ECCV 1998 pp. 796-808
doi:10.1007/BFB0054780 /eccv/1998/kanatani1998eccv-optimal/

Abstract

We discuss optimal estimation of the current location of a robot by matching an image of the scene taken by the robot with the model of the environment. We first present a theoretical accuracy bound and then give a method that attains that bound, which can be viewed as describing the probability distribution of the current location. Using real images, we demonstrate that our method is superior to the naive least-squares method. We also confirm the theoretical predictions of our theory by applying the bootstrap procedure.

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Cite

Text

Kanatani and Ohta. "Optimal Robot Self-Localization and Reliability Evaluation." European Conference on Computer Vision, 1998. doi:10.1007/BFB0054780

Markdown

[Kanatani and Ohta. "Optimal Robot Self-Localization and Reliability Evaluation." European Conference on Computer Vision, 1998.](https://mlanthology.org/eccv/1998/kanatani1998eccv-optimal/) doi:10.1007/BFB0054780

BibTeX

@inproceedings{kanatani1998eccv-optimal,
  title     = {{Optimal Robot Self-Localization and Reliability Evaluation}},
  author    = {Kanatani, Ken-ichi and Ohta, Naoya},
  booktitle = {European Conference on Computer Vision},
  year      = {1998},
  pages     = {796-808},
  doi       = {10.1007/BFB0054780},
  url       = {https://mlanthology.org/eccv/1998/kanatani1998eccv-optimal/}
}