一种计算凸多面体Minkowski差分的新算法

H. Barki, Florence Denis, F. Dupont
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引用次数: 4

摘要

基于贡献顶点的概念,提出了一种精确、高效计算凸多面体闵可夫斯基差分的新算法。首先,我们扩展了Minkowski差分情况下贡献顶点的概念。然后,我们利用计算的贡献顶点提供的信息生成Minkowski差面超集。最后,通过对生成的超集进行裁剪,计算Minkowski差分多面体。我们比较了基于贡献顶点的Minkowski差分(CVMD)算法和基于Nef多面体的方法,使用Minkowski加法、补码、换位和并运算。性能基准测试表明,CVMD算法优于间接Nef多面体算法。我们所有的实现都使用精确的数字类型,产生精确的结果,并基于CGAL,即计算几何算法库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Algorithm for the Computation of the Minkowski Difference of Convex Polyhedra
We present a new algorithm, based on the concept of contributing vertices, for the exact and efficient computation of the Minkowski difference of convex polyhedra. First, we extend the concept of contributing vertices for the Minkowski difference case. Then, we generate a Minkowski difference facets superset by exploiting the information provided by the computed contributing vertices. Finally, we compute the Minkowski difference polyhedron through the trimming of the generated superset. We compared our Contributing Vertices-based Minkowski Difference (CVMD) algorithm to a Nef polyhedra-based approach using Minkowski addition, complement, transposition, and union operations. The performance benchmark shows that our CVMD algorithm outperforms the indirect Nef polyhedra-based approach. All our implementations use exact number types, produce exact results, and are based on CGAL, the Computational Geometry Algorithms Library.
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