In industrial assembly, a registration mark can be placed on parts to aid a computer vision system in determining the position and orientation (pose) of parts. However, when sensor noise and limits on resolution introduce errors in the measured location of the registration mark, these errors can propagate into the measurement of part pose. In this paper, the authors define the registration mark problem: given an n-sided rigid planar polygonal part and a set of k poses for the part, locate a point on the surface of the part that maximizes the minimum distance between transformed points. A registration mark at this point will be maximally robust to sensor imperfections. The authors give an O(n log n+k/sup 4/ log k:log* k) time algorithm to solve this planar problem using a result from Schwartz and Sharir (see J. Symbolic Computation, vol.10, p.371-93, 1990), and demonstrate the algorithm using a commercial vision system. The results extend to classes of curved planar parts and polyhedral parts.
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机译：在工业装配中，可以在零件上放置定位标记，以帮助计算机视觉系统确定零件的位置和方向（姿势）。但是，当传感器噪音和分辨率限制在套准标记的测量位置引入误差时，这些误差会传播到零件姿态的测量中。在本文中，作者定义了套准标记问题：给定一个n边的刚性平面多边形零件，并为该零件设置一组k姿势，在零件表面上定位一个点，该点可使变换点之间的最小距离最大。此时的对准标记将最大程度地防止传感器缺陷。作者给出了O（n log n + k / sup 4 / log k：log * k）时间算法，以使用Schwartz和Sharir的结果来解决该平面问题（请参见J. Symbolic Computation，第10卷，第371页） -93，1990年），并演示了使用商用视觉系统的算法。结果扩展到弯曲的平面零件和多面体零件的类别。
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