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A flexible camera positioning strategy for robot-based visual inspection applications

机译:灵活的摄像机定位策略,用于基于机器人的视觉检查应用

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This paper presents a flexible camera positioning strategy to deal with unknown object poses in a visual inspection application. The object's CAD model is used in a view-based strategy to estimate the object pose. An effective lookup table method is adopted to speed up the estimation. The principal component analysis (PCA) is used to reduce the lookup table size and save memory space. Compared with those edge-based approaches which require good initial pose estimation, our method can find the initial pose in a large range without any initial guess. With the pose estimation precise Eye-in-Hand camera positioning is realized by homography-based visual servo to inspect the object. The inspection strategy with unknown object poses is described in detail. Experiments are carried out to evaluate the system performances.
机译:本文提出了一种灵活的摄像机定位策略,以处理视觉检查应用程序中未知的物体姿势。在基于视图的策略中使用对象的CAD模型来估计对象的姿势。采用有效的查找表方法来加快估计速度。主成分分析(PCA)用于减小查找表的大小并节省内存空间。与那些需要良好初始姿态估计的基于边缘的方法相比,我们的方法可以在很大范围内找到初始姿态而无需任何初始猜测。借助姿势估计,基于单应性的视觉伺服可实现对手持摄像机的精确定位,从而对物体进行检查。详细介绍了带有未知物体姿态的检查策略。进行实验以评估系统性能。

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