M.I.T. Artificial Intelligence Laboratory, 545 Technology Square, Cambridge, MA 02139.
IEEE Trans Pattern Anal Mach Intell. 1987 Apr;9(4):469-82. doi: 10.1109/tpami.1987.4767935.
This paper discusses how local measurements of positions and surface normals may be used to identify and locate overlapping objects. The objects are modeled as polyhedra (or polygons) having up to six degrees of positional freedom relative to the sensors. The approach operates by examining all hypotheses about pairings between sensed data and object surfaces and efficiently discarding inconsistent ones by using local constraints on: distances between faces, angles between face normals, and angles (relative to the surface normals) of vectors between sensed points. The method described here is an extension of a method for recognition and localization of nonoverlapping parts previously described in [18] and [15].
本文讨论了如何利用局部位置和表面法向量测量值来识别和定位重叠物体。这些物体被建模为具有六个自由度的多面体（或多边形），相对于传感器的位置。该方法通过检查所有关于感测数据与物体表面之间的配对假设，并通过使用局部约束（面之间的距离、法向量之间的角度以及感测点之间的向量相对于表面法向量的角度）有效地消除不一致的假设来工作。这里描述的方法是先前在 [18] 和 [15] 中描述的用于识别和定位非重叠部分的方法的扩展。
