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Visual Servoing Based on Shifted Moments

机译:基于位移矩的视觉伺服

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摘要

Over the past decade, image moments have been exploited in several visual servoing schemes for their ability to represent object regions, objects defined by contours or a set of discrete points. Moments have also been useful to achieve control decoupling properties and to choose a minimal number of features to control the whole degrees of freedom (DOFs) of a camera. However, the choice of moment-based features to control the rotational motions around the -axis and -axis simultaneously with the translational motions along the same axis remains a key issue. In this paper, we introduce new visual features computed from low-order “shifted moments invariant.” Importantly, they allow us 1) to define a unique combination of visual features to control the whole six DOFs of an eye-in-hand camera independently from the object shape and (2) to significantly enlarge the convergence domain of the closed-loop system.
机译:在过去的十年中,图像矩已经在几种视觉伺服方案中得到了利用,因为它们具有表示对象区域,轮廓定义的对象或一组离散点的能力。力矩对于实现控制解耦特性以及选择最少数量的功能来控制摄像机的整个自由度(DOF)也很有用。但是,选择基于力矩的特征来控制围绕-轴和-轴的旋转运动以及沿着同一轴的平移运动同时仍然是一个关键问题。在本文中,我们介绍了根据低阶“位移矩不变”计算出的新视觉特征。重要的是,它们使我们能够:1)定义视觉特征的独特组合,以独立于物体形状来控制手持摄像机的整个六个自由度,以及(2)显着扩大闭环系统的收敛域。

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