Optimal Least-Squares Solution to the Hand-Eye Calibration Problem
Abstract
We propose a least-squares formulation to the noisy hand-eye calibration problem using dual-quaternions, and introduce efficient algorithms to find the exact optimal solution, based on analytic properties of the problem, avoiding non-linear optimization. We further present simple analytic approximate solutions which provide remarkably good estimations compared to the exact solution. In addition, we show how to generalize our solution to account for a given extrinsic prior in the cost function. To the best of our knowledge our algorithm is the most efficient approach to optimally solve the hand-eye calibration problem.
Cite
Text
Dekel et al. "Optimal Least-Squares Solution to the Hand-Eye Calibration Problem." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.01361Markdown
[Dekel et al. "Optimal Least-Squares Solution to the Hand-Eye Calibration Problem." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/dekel2020cvpr-optimal/) doi:10.1109/CVPR42600.2020.01361BibTeX
@inproceedings{dekel2020cvpr-optimal,
title = {{Optimal Least-Squares Solution to the Hand-Eye Calibration Problem}},
author = {Dekel, Amit and Harenstam-Nielsen, Linus and Caccamo, Sergio},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2020},
doi = {10.1109/CVPR42600.2020.01361},
url = {https://mlanthology.org/cvpr/2020/dekel2020cvpr-optimal/}
}