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2 1/2 D visual servoing with respect to unknown objects through a new estimation scheme of camera displacement

机译:通过摄像机位移的新估计方案对未知物体进行2 1/2 D视觉伺服

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Classical visual servoing techniques need a strong a priori knowledge of the shape and the dimensions of the observed objects. In this paper, we present how the 2 1/2 D visual servoing scheme we have recently developed, can be used with unknown objects characterized by a set of points. Our scheme is based on the estimation of the camera displacement from two views, given by the current and desired images. Since vision-based robotics tasks generally necessitate to be performed at video rate, we focus only on linear algorithms. Classical linear methods are based on the computation of the essential matrix. In this paper, we propose a different method, based on the estimation of the homography matrix related to a virtual plane attached to the object. We show that our method provides a more stable estimation when the epipolar geometry degenerates. This is particularly important in visual servoing to obtain a stable control law, especially near the convergence of the system. Finally, experimental results confirm the improvement in the stability, robustness, and behaviour of our scheme with respect to classical methods. [References: 32]
机译:经典的视觉伺服技术需要对被观察物体的形状和尺寸有很强的先验知识。在本文中,我们介绍了我们最近开发的2 1/2 D视觉伺服方案如何与以一组点为特征的未知对象一起使用。我们的方案基于从当前和所需图像给出的两个视图对摄像机位移的估计。由于基于视觉的机器人技术任务通常必须以视频速率执行,因此我们仅关注线性算法。经典的线性方法基于基本矩阵的计算。在本文中,我们基于与附着到对象的虚拟平面有关的单应性矩阵的估计,提出了一种不同的方法。我们表明,当对极几何形状退化时,我们的方法提供了更稳定的估计。这对于视觉伺服以获得稳定的控制律尤其重要,尤其是在系统收敛附近。最后,实验结果证实了我们的方案相对于经典方法在稳定性,鲁棒性和行为方面的改进。 [参考:32]

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