Intersection Searching Amid Tetrahedra in 4-Space and Efficient Continuous Collision Detection

Authors Esther Ezra , Micha Sharir

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Esther Ezra
  • School of Computer Science, Bar Ilan University, Ramat Gan, Israel
Micha Sharir
  • School of Computer Science, Tel Aviv University, Tel Aviv, Israel

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Esther Ezra and Micha Sharir. Intersection Searching Amid Tetrahedra in 4-Space and Efficient Continuous Collision Detection. In 30th Annual European Symposium on Algorithms (ESA 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 244, pp. 51:1-51:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


We develop data structures for intersection detection queries in four dimensions that involve segments, triangles and tetrahedra. Specifically, we study two main problems: (i) Preprocess a set of n tetrahedra in {ℝ}⁴ into a data structure for answering segment-intersection queries amid the given tetrahedra (referred to as segment-tetrahedron intersection queries), and (ii) Preprocess a set of n triangles in {ℝ}⁴ into a data structure that supports triangle-intersection queries amid the input triangles (referred to as triangle-triangle intersection queries). As far as we can tell, these problems have not been previously studied. For problem (i), we first present a "standard" solution which, for any prespecified value n ≤ s ≤ n⁶ of a so-called storage parameter s, yields a data structure with O^*(s) storage and expected preprocessing, which answers an intersection query in O^*(n/s^{1/6}) time (here and in what follows, the O^*(⋅) notation hides subpolynomial factors). For problem (ii), using similar arguments, we present a solution that has the same asymptotic performance bounds. We then improve the solution for problem (i), and present a more intricate data structure that uses O^*(n²) storage and expected preprocessing, and answers a segment-tetrahedron intersection query in O^*(n^{1/2}) time. Using the parametric search technique of Agarwal and Matoušek [P. K. Agarwal and J. Matoušek, 1993], we can obtain data structures with similar performance bounds for the ray-shooting problem amid tetrahedra in {ℝ}⁴. Unfortunately, so far we do not know how to obtain a similar improvement for problem (ii). Our algorithms are based on a primal-dual technique for range searching with semi-algebraic sets, based on recent advances in this area [P. K. Agarwal et al., 2021; J. Matoušek and Z. Patáková, 2015]. As this is a result of independent interest, we spell out the details of this technique. As an application, we present a solution to the problem of "continuous collision detection" amid moving tetrahedra in 3-space. That is, the workspace consists of n tetrahedra, each moving at its own fixed velocity, and the goal is to detect a collision between some pair of moving tetrahedra. Using our solutions to problems (i) and (ii), we obtain an algorithm that detects a collision in O^*(n^{12/7}) expected time. We also present further applications, including an output-sensitive algorithm for constructing the arrangement of n tetrahedra in ℝ⁴ and an output-sensitive algorithm for constructing the intersection or union of two or several nonconvex polyhedra in ℝ⁴.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Computational geometry
  • Ray shooting
  • Tetrahedra in {ℝ}⁴
  • Intersection queries in {ℝ}⁴
  • Polynomial partitioning
  • Range searching
  • Semi-algebraic sets
  • Tradeoff


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