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A contact detection algorithm for superellipsoids based on the common‐normal concept

A contact detection algorithm for superellipsoids based on the common‐normal concept Purpose – The paper aims to introduce an efficient contact detection algorithm for smooth convex particles. Design/methodology/approach – The contact points of adjacent particles are defined according to the common‐normal concept. The problem of contact detection is formulated as 2D unconstrained optimization problem that is solved by a combination of Newton's method and a Levenberg‐Marquardt method. Findings – The contact detection algorithm is efficient in terms of the number of iterations required to reach a high accuracy. In the case of non‐penetrating particles, a penetration can be ruled out in the course of the iterative solution before convergence is reached. Research limitations/implications – The algorithm is only applicable to smooth convex particles, where a bijective relation between the surface points and the surface normals exists. Originality/value – By a new kind of formulation, the problem of contact detection between 3D particles can be reduced to a 2D unconstrained optimization problem. This formulation enables fast contact exclusions in the case of non‐penetrating particles. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Engineering Computations: International Journal for Computer-Aided Engineering and Software Emerald Publishing

A contact detection algorithm for superellipsoids based on the common‐normal concept

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References (24)

Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
0264-4401
DOI
10.1108/02644400810881374
Publisher site
See Article on Publisher Site

Abstract

Purpose – The paper aims to introduce an efficient contact detection algorithm for smooth convex particles. Design/methodology/approach – The contact points of adjacent particles are defined according to the common‐normal concept. The problem of contact detection is formulated as 2D unconstrained optimization problem that is solved by a combination of Newton's method and a Levenberg‐Marquardt method. Findings – The contact detection algorithm is efficient in terms of the number of iterations required to reach a high accuracy. In the case of non‐penetrating particles, a penetration can be ruled out in the course of the iterative solution before convergence is reached. Research limitations/implications – The algorithm is only applicable to smooth convex particles, where a bijective relation between the surface points and the surface normals exists. Originality/value – By a new kind of formulation, the problem of contact detection between 3D particles can be reduced to a 2D unconstrained optimization problem. This formulation enables fast contact exclusions in the case of non‐penetrating particles.

Journal

Engineering Computations: International Journal for Computer-Aided Engineering and Software – Emerald Publishing

Published: Jul 18, 2008

Keywords: Computational geometry; Motion

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