Randomized Incremental Construction of Delaunay Triangulations of Nice Point Sets

Randomized incremental construction (RIC) is one of the most important paradigms for building geometric data structures. Clarkson and Shor developed a general theory that led to numerous algorithms which are both simple and efficient in theory and in practice. Randomized incremental constructions are usually space-optimal and time-optimal in the worst case, as exemplified by the construction of convex hulls, Delaunay triangulations, and arrangements of line segments. However, the worst-case scenario occurs rarely in practice and we would like to understand how RIC behaves when the input is nice in the sense that the associated output is significantly smaller than in the worst case. For example, it is known that the Delaunay triangulation of nicely distributed points in $${\mathbb {E}}^d$$ E d or on polyhedral surfaces in $${\mathbb {E}}^3$$ E 3 has linear complexity, as opposed to a worst-case complexity of $$\Theta (n^{\lfloor d/2\rfloor })$$ Θ ( n ⌊ d / 2 ⌋ ) in the first case and quadratic in the second. The standard analysis does not provide accurate bounds on the complexity of such cases and we aim at establishing such bounds in this paper. More precisely, we will show that, in the two cases above and variants of them, the complexity of the usual RIC is $$O(n\log n)$$ O ( n log n ) , which is optimal. In other words, without any modification, RIC nicely adapts to good cases of practical value. At the heart of our proof is a bound on the complexity of the Delaunay triangulation of random subsets of $${\varepsilon }$$ ε -nets. Along the way, we prove a probabilistic lemma for sampling without replacement, which may be of independent interest.

Discrete-Space Analysis of Partial Differential Equations

There are numerous examples that arise and benefit from the reachability analysis problem. In cyber-physical systems (CPS), most dynamic phenomena are described as systems of ordinary differential equations (ODEs). Previous work has been done using zonotopes, support functions, and other geometric data structures to represent subsets of the reachable set and have been shown to be efficient. Meanwhile, a wide range of important control problems are more precisely modeled by partial differential equations (PDEs), even though not much attention has been paid to their reachability analyses. This reason motivates us to investigate the properties of these equations, especially from the reachability analysis and verification perspectives. In contrast to ODEs, PDEs have other space variables that also affect their behaviors and are more complex. In this paper, we study the discrete-space analysis of PDEs. Our ultimate goal is to propose a set of PDE reachability analysis benchmarks, and present preliminary analysis of different dimensional heat equations and wave equations. Finite difference methods (FDMs) are utilized to approximate the derivative at each mesh point with explicit order of errors. FDM will convert the PDE to a system of ODEs depending on the type of boundary conditions and discretization scheme chosen. After that, the problem can be treated as a common reachability problem and relevant conceptions and approaches can be applied and evaluated directly. We used SpaceEx to generate the plots and reachable regions for these equations given inputs and the series of results are shown and analyzed.

Deterministic mathematical morphology for CAD/CAM

Purpose – The purpose of this paper is to present a new geometric model based on the mathematical morphology paradigm, specialized to provide determinism to the classic morphological operations. The determinism is needed to model dynamic processes that require an order of application, as is the case for designing and manufacturing objects in CAD/CAM environments. Design/methodology/approach – The basic trajectory-based operation is the basis of the proposed morphological specialization. This operation allows the definition of morphological operators that obtain sequentially ordered sets of points from the boundary of the target objects, inexistent determinism in the classical morphological paradigm. From this basic operation, the complete set of morphological operators is redefined, incorporating the concept of boundary and determinism: trajectory-based erosion and dilation, and other morphological filtering operations. Findings – This new morphological framework allows the definition of complex three-dimensional objects, providing arithmetical support to generating machining trajectories, one of the most complex problems currently occurring in CAD/CAM. Originality/value – The model proposes the integration of the processes of design and manufacture, so that it avoids the problems of accuracy and integrity that present other classic geometric models that divide these processes in two phases. Furthermore, the morphological operative is based on points sets, so the geometric data structures and the operations are intrinsically simple and efficient. Another important value that no excessive computational resources are needed, because only the points in the boundary are processed.