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一种用于惯性约束聚变实验中诊断包精细定位的方法。

A method for fine positioning of diagnostic packages in inertial confinement fusion experiments.

作者信息

Wang Wei, Shi Tielin, Lee Kok-Meng

机构信息

School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.

出版信息

Rev Sci Instrum. 2011 Dec;82(12):125113. doi: 10.1063/1.3669780.

Abstract

A method based on binocular vision servoing for positioning of a diagnostic package in inertial confinement fusion (ICF) experiments is presented. The general diagnostic instrument manipulator will provide precision three dimension positioning and alignment-to-target capability in ICF experiments. In this work, we focus on the final precise automatic positioning with a binocular vision system. A three dimension image projection vector (IPV), which has an almost linear relationship with the target position in 3D space under the condition of weak perspective, is introduced to extract target position information from binocular image. The difference of the IPV between the current image and the desired image will be used as the input of servo controller. A differential motion model was found for the hybrid manipulator with three degrees of freedom. With this model and the said IPV, the servo strategy will be dramatically simplified compare with general image based visual servo in which the image Jacobian matrix needs estimated online. The experiment result implies that the locating accuracy of the manipulator is less than two pixels. This method can also be used in micromanipulation visual servo field.

摘要

提出了一种基于双目视觉伺服的惯性约束聚变(ICF)实验中诊断包定位方法。通用诊断仪器操纵器将在ICF实验中提供精确的三维定位和目标对准能力。在这项工作中,我们专注于利用双目视觉系统进行最终的精确自动定位。引入了三维图像投影向量(IPV),在弱透视条件下,它与三维空间中的目标位置几乎呈线性关系,用于从双目图像中提取目标位置信息。当前图像与期望图像之间的IPV差异将用作伺服控制器的输入。找到了一种具有三个自由度的混合操纵器的差动运动模型。利用该模型和上述IPV,与需要在线估计图像雅可比矩阵的一般基于图像的视觉伺服相比,伺服策略将大大简化。实验结果表明,操纵器的定位精度小于两个像素。该方法也可用于微操作视觉伺服领域。

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