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Hand-Eye Calibration without Hand Orientation Measurement Using Minimal Solution

机译:使用最小溶液无需手动取向测量的手眼校准

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In this paper we solve the problem of estimating the relative pose between a robot's gripper and a camera mounted rigidly on the grip-per in situations where the rotation of the gripper w.r.t. the robot global coordinate system is not known. It is a variation of the so called hand-eye calibration problem. We formulate it as a problem of seven equations in seven unknowns and solve it using the Grobner basis method for solving systems of polynomial equations. This enables us to calibrate from the minimal number of two relative movements and to provide the first exact algebraic solution to the problem. Further, we describe a method for selecting the geometrically correct solution among the algebraically correct ones computed by the solver. In contrast to the previous iterative methods, our solution works without any initial estimate and has no problems with error accumulation. Finally, by evaluating our algorithm on both synthetic and real scene data we demonstrate that it is fast, noise resistant, and numerically stable.
机译:在本文中,我们解决刚性地安装在情况夹具估计机器人的夹持器和相机之间的相对姿势的问题,其中夹持器w.r.t.的旋转机器人全局坐标系不知道。它是所谓的手眼校准问题的变化。我们将其制定为七个未知数七个方程的问题,并使用Grobner基础方法解决了多项式方程的系统。这使我们能够从最小相对运动的最小数量校准,并为问题提供第一精确的代数解决方案。此外,我们描述了一种用于选择由求解器计算的代数正确的解决方案中的几何正确解决方案的方法。与前一个迭代方法相比,我们的解决方案在没有任何初始估计的情况下工作,并且没有错误累积问题。最后,通过在合成和真实场景数据上评估我们的算法,我们证明它是快速,抗噪声和数值稳定的。

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