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Proximity structures for moving objects in constrained and unconstrained environments.

机译:在受约束和不受约束的环境中移动对象的邻近结构。

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Proximity structures are of central importance in Computational Geometry. They appear in several applications such as robotics, motion planning, collision detection and also in simulations of virtual and physical systems. In the real world, in most of these applications the geometric objects involved are often moving. It is thus essential to be able to maintain in an efficient way proximity structures for moving objects.; In this thesis we deal with two kinds of proximity structures: sparse spanner graphs and Voronoi diagrams. We prove that bounded aspect ratio triangulations in two and three dimensions are spanner graphs. We also show that both conforming two-dimensional bounded aspect ratio triangulations and the Constrained Delaunay triangulation are spanner graphs.; Using the Kinetic Data Structures (KDS) framework, we show how to maintain near neighbors for moving points in two and three dimensions when the underlying structure is the Voronoi diagram. In the more realistic case of a set of possibly intersecting disks moving on the plane we show how to maintain the Euclidean Voronoi diagram. Using then the Voronoi diagram as a basis, we describe how to maintain the closest pair of the set of disks, a spanning sub-graph of the connectivity graph of the set of disks and near neighbors of disks.; Finally, we discuss the problem of handling kinetic simulations of geometric objects whose motion is represented as polynomials of high degree. In this setting, the moments in time that a change happens in the combinatorial structure of the attribute of interest are roots of polynomials of high degree. We present an algorithm that speeds up the kinetic simulations by representing the roots of the afore-mentioned polynomials as intervals, instead of computing them explicitly.
机译:邻近结构在计算几何中至关重要。它们出现在多种应用中,例如机器人技术,运动计划,碰撞检测以及虚拟和物理系统的仿真。在现实世界中,在大多数这些应用程序中,涉及的几何对象经常在移动。因此,至关重要的是能够以有效的方式保持用于移动物体的邻近结构。在本文中,我们处理两种邻近结构:稀疏扳手图和Voronoi图。我们证明二维和三维的有界长宽比三角剖分是扳手图。我们还表明,符合二维有界长宽比三角剖分和约束Delaunay三角剖分都是扳手图。使用动力学数据结构(KDS)框架,我们展示了当基础结构为Voronoi图时,如何为二维和三维维的移动点保持近邻。在一组可能相交的磁盘在平面上移动的更现实的情况下,我们展示了如何维护欧几里得Voronoi图。然后,以Voronoi图为基础,描述如何维护磁盘组中最接近的磁盘对,磁盘组连接性图的跨度子图以及邻近的磁盘。最后,我们讨论了处理几何对象的动力学模拟的问题,这些对象的运动表示为高次多项式。在这种情况下,关注属性的组合结构发生变化的时刻是高次多项式的根。我们提出了一种算法,该算法通过将上述多项式的根表示为间隔而不是显式地计算它们来加快动力学模拟。

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