Optimal least-squares solution to the hand-eye calibration problem

Amit Dekel, Linus Harenstam-Nielsen, Sergio Caccamo; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 13598-13606

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.

Related Material


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[bibtex]
@InProceedings{Dekel_2020_CVPR,
author = {Dekel, Amit and Harenstam-Nielsen, Linus and Caccamo, Sergio},
title = {Optimal least-squares solution to the hand-eye calibration problem},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}