Robust solid modeling by avoiding redundancy for manifold objects in boundary representation

Journal ArticleThis paper describes a new approach to the robustness problem in solid modeling. We identify as t h e main cause of t h e lack of robustness that interdependent topological relations are derived from approximate data. Disregarding the interdependencies very likely violates basic properties, such as reflexivity, and transitivity, resulting in invalid data representations, such as dangling edges, missing faces, etc. We show that the boundary of manifold objects can be represented without redundant relations which avoids inconsistencies. An algorithm for regularized set operations for manifold solids which is based on the principle of avoiding and eliminating redundancy is described. This algorithm has been implemented for objects bounded by planar and natural quadric surfaces; it handles coincidence and incidence cases between surfaces and curves robustly

A new approach to tolerance analysis

Journal ArticleTolerance analysis is seen as part of a more general problem, namely handling data with uncertainty. Uncertain geometric data arises when interpreting measured data, but also in solid modeling where floating point approximations are common, when representing design tolerances, or when dealing with limited manufacturing precision. The common question is whether parts with uncertain shape fulfill certain functional specification. The question is expressed as geometrical relationship between toleranced objects. Unfortunately, tolerance based relations are often inconsistent, unlike relations between exactly represented objects. In this paper we survey current tolerance representation and analysis methods. We then derive our method of intuitionistic tolerance handling from a method developed for robust solid modeling. A new representational framework is proposed, which serves as the basis for robust geometric modeling and tolerance analysis. We illustrate the framework with examples of assembly design

Technology 2002: The Third National Technology Transfer Conference and Exposition, volume 2

Proceedings from symposia of the Technology 2002 Conference and Exposition, December 1-3, 1992, Baltimore, MD. Volume 2 features 60 papers presented during 30 concurrent sessions

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Techniques de bas niveau en traitement d'images pour la télédétection des milieux non homogènes

La télédétection vise à acquérir l'information sur des cibles en étudiant leur réponse aux ondes électromagnétiques. Et partout nous rencontrons des milieux non homogènes et des composites. Connaître comment ces milieux non homogènes répondent a la sonde de télédétection est de la plus grande importance pour la praticabilité même de la télédétection. Le comportement macroscopique d'un composite peut séxprimer en fonction des caractéristiques macroscopiques de ses constituants, mais d'une manière complexe incluant la géométrie de leur arrangement. Si nous pouvons obtenir le tenseur diélectrique efficace d'un composé, nous pouvons modéliser sa réponse au champ électromagnétique, et donc sa réponse comme cible de télédétection. La nécessité pour inclure la géométrie détaillée du système d'une façon efficace dans des méthodes numériques, ainsi qu'une équivalence entre les images numériques et les modèles de treillis des composites, suggère le recours aux techniques de bas niveau de traitement d'images numériques. Le cadre de cette thèse est le traitement numérique d'un problème général de télédétection fondée sur le problème électromagnétique d'homogénéisation dans des microstructures. Dans ce contexte, deux techniques de traitement d'images de bas niveau sont présentées, à savoir, une nouvelle méthode pour l'étiquetage des composantes connexes, présentant des améliorations significatives par rapport aux méthodes existantes, et une méthode de codage des configurations locales avec plusieurs caractéristiques la rendant appropriée pour des applications variées. Leurs avantages sont discutés, et des exemples d'application sont fournis au-delà du domaine spécifique étant à leur origine, comme la vision artificielle, le codage d'image, ou encore la synthèse d'image.The aim of remote sensing is obtaining information about targets by studying their response to electromagnetic waves. And everywhere we found non homogeneous media. Knowing how these non homogeneous media respond to the remote sensing probe is of great importance for the very feasibility of remote sensing. The macroscopic behaviour of a composite can be expressed as a function of the macroscopic characteristics of its constituents, but usually in a complex way which includes the geometry of their arrangement. If we are able to obtain the effective permittivity tensor of any given composite, we can model its macroscale response to the electromagnetic field, and therefore its response as a remote sensing target. The necessity of including the detailed geometry of the system in an efficient way in the numerical methods, together with an equivalence between grid models and digital images, suggest the recourse to low level image processing techniques. The framework of this thesis is the numerical treatment of a general problem in remote sensing based on the electromagnetic problem of homogenization of microstructures. In this context, two low level image processing techniques are presented, a new method for the labelling of connected components, with significant advantages over the classical methods, and a local configuration encoding scheme with characteristics which render it useful for different applications. Their advantages and applicability are discussed, together with some examples of application in fields out of the scope of the specific problem which originated them, namely computer vision, image coding, and image synthesis

Data-Driven Methods to Build Robust Legged Robots

For robots to ever achieve signicant autonomy, they need to be able to mitigate performance loss due to uncertainty, typically from a novel environment or morphological variation of their bodies. Legged robots, with their complex dynamics, are particularly challenging to control with principled theory. Hybrid events, uncertainty, and high dimension are all confounding factors for direct analysis of models. On the other hand, direct data-driven methods have proven to be equally dicult to employ. The high dimension and mechanical complexity of legged robots have proven challenging for hardware-in-the-loop strategies to exploit without signicant eort by human operators. We advocate that we can exploit both perspectives by capitalizing on qualitative features of mathematical models applicable to legged robots, and use that knowledge to strongly inform data-driven methods. We show that the existence of these simple structures can greatly facilitate robust design of legged robots from a data-driven perspective. We begin by demonstrating that the factorial complexity of hybrid models can be elegantly resolved with computationally tractable algorithms, and establish that a novel form of distributed control is predicted. We then continue by demonstrating that a relaxed version of the famous templates and anchors hypothesis can be used to encode performance objectives in a highly redundant way, allowing robots that have suffered damage to autonomously compensate. We conclude with a deadbeat stabilization result that is quite general, and can be determined without equations of motion.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155053/1/gcouncil_1.pd