使用3D点进行连续手眼校准

Bjarne Großmann, V. Krüger
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引用次数: 5

摘要

最近校准算法的发展主要有两个方向:(1)提高数学方法的准确性;(2)通过减少对校准对象的依赖来增加使用的灵活性。然而,这两种趋势似乎是矛盾的,因为整体精度与校准对象的姿态估计精度直接相关,因此需要大的对象,而灵活性的增加导致更小的对象或更嘈杂的估计方法。本文提出的方法旨在分两步解决这个问题:首先,我们推导了一个简单的封闭形式的解,将焦点转移到只解决必要的手眼转换的平移方程。结果表明,与传统方法相比,该方法在精度和鲁棒性方面都具有优越性。其次,我们通过使用基于平移方程的类似公式将对校准对象的依赖降低到单个3d点,该公式受校准对象方向估计误差的影响较小。此外,它使方向估计过时,同时利用了第一种解决方案的更高精度和鲁棒性,从而产生了一种通用的连续手眼校准方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Continuous hand-eye calibration using 3D points
The recent development of calibration algorithms has been driven into two major directions: (1) an increasing accuracy of mathematical approaches and (2) an increasing flexibility in usage by reducing the dependency on calibration objects. These two trends, however, seem to be contradictory since the overall accuracy is directly related to the accuracy of the pose estimation of the calibration object and therefore demanding large objects, while an increased flexibility leads to smaller objects or noisier estimation methods. The method presented in this paper aims to resolves this problem in two steps: First, we derive a simple closed-form solution with a shifted focus towards the equation of translation that only solves for the necessary hand-eye transformation. We show that it is superior in accuracy and robustness compared to traditional approaches. Second, we decrease the dependency on the calibration object to a single 3D-point by using a similar formulation based on the equation of translation which is much less affected by the estimation error of the calibration object's orientation. Moreover, it makes the estimation of the orientation obsolete while taking advantage of the higher accuracy and robustness from the first solution, resulting in a versatile method for continuous hand-eye calibration.
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