7,365 research outputs found
A Convex Polynomial Force-Motion Model for Planar Sliding: Identification and Application
We propose a polynomial force-motion model for planar sliding. The set of
generalized friction loads is the 1-sublevel set of a polynomial whose gradient
directions correspond to generalized velocities. Additionally, the polynomial
is confined to be convex even-degree homogeneous in order to obey the maximum
work inequality, symmetry, shape invariance in scale, and fast invertibility.
We present a simple and statistically-efficient model identification procedure
using a sum-of-squares convex relaxation. Simulation and robotic experiments
validate the accuracy and efficiency of our approach. We also show practical
applications of our model including stable pushing of objects and free sliding
dynamic simulations.Comment: 2016 IEEE International Conference on Robotics and Automation (ICRA
Randomized algorithms for statistical image analysis and site percolation on square lattices
We propose a novel probabilistic method for detection of objects in noisy
images. The method uses results from percolation and random graph theories. We
present an algorithm that allows to detect objects of unknown shapes in the
presence of random noise. The algorithm has linear complexity and exponential
accuracy and is appropriate for real-time systems. We prove results on
consistency and algorithmic complexity of our procedure.Comment: Submitted for publication on December 11, 200
Multiscale Phenomenology of the Cosmic Web
We analyze the structure and connectivity of the distinct morphologies that
define the Cosmic Web. With the help of our Multiscale Morphology Filter (MMF),
we dissect the matter distribution of a cosmological CDM N-body
computer simulation into cluster, filaments and walls. The MMF is ideally
suited to adress both the anisotropic morphological character of filaments and
sheets, as well as the multiscale nature of the hierarchically evolved cosmic
matter distribution. The results of our study may be summarized as follows:
i).- While all morphologies occupy a roughly well defined range in density,
this alone is not sufficient to differentiate between them given their overlap.
Environment defined only in terms of density fails to incorporate the intrinsic
dynamics of each morphology. This plays an important role in both linear and
non linear interactions between haloes. ii).- Most of the mass in the Universe
is concentrated in filaments, narrowly followed by clusters. In terms of
volume, clusters only represent a minute fraction, and filaments not more than
9%. Walls are relatively inconspicous in terms of mass and volume. iii).- On
average, massive clusters are connected to more filaments than low mass
clusters. Clusters with M h have on average
two connecting filaments, while clusters with M
h have on average five connecting filaments. iv).- Density profiles
indicate that the typical width of filaments is 2\Mpch. Walls have less well
defined boundaries with widths between 5-8 Mpc h. In their interior,
filaments have a power-law density profile with slope ,
corresponding to an isothermal density profile.Comment: 28 pages, 22 figures, accepted for publication in MNRAS. For a
high-res version see http://www.astro.rug.nl/~weygaert/webmorph_mmf.pd
An investigation on methods for axis detection of high-density generic axially symmetric mechanical surfaces for automatic geometric inspection
none2noThe detection of the symmetry axis from discrete axially symmetric surfaces is an interesting topic, which is transversal to various fields: from geometric inspection to reverse engineering, archeology, etc. In the literature, several approaches have been proposed for estimating the axis from high-density triangular models of surfaces acquired by three-dimensional (3D) scanning. The axis evaluation from discrete models is, in fact, a very complex task to accomplish, due to several factors that inevitably influence the quality of the estimation and the accuracy of the measurements and evaluations depending on it. The underlying principle of each one of these approaches takes advantage of a specific property of axially symmetric surfaces. No investigations, however, have been carried out so far in order to support in the selection of the most suitable algorithms for applications aimed at automatic geometric inspection. In this regard, ISO standards currently do not provide indications on how to perform the axis detection in the case of generic axially symmetric surfaces, limiting themselves to addressing the issue only in the case of cylindrical or conical surfaces. This paper first provides an overview of the approaches that can be used for geometric inspection purposes; then, it applies them to various case studies involving one or more generic axially symmetric surfaces, functionally important and for which the axis must be detected since necessary for geometric inspection. The aim is to compare, therefore, the performances of the various methodologies by trying to highlight the circumstances in which these ones may fail. Since this investigation requires a reference (i.e. the knowledge of the true axis), the methodologies have been applied to discrete models suitably extracted from CAD surfaces.openE Guardiani; A MorabitoGuardiani, E; Morabito,
Reducing “Structure from Motion”: a general framework for dynamic vision. 1. Modeling
The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of apparently unrelated models and estimation techniques. We propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction. The “natural” dynamic model, derived from the rigidity constraint and the projection model, is first reduced by explicitly decoupling structure (depth) from motion. Then, implicit decoupling techniques are explored, which consist of imposing that some function of the unknown parameters is held constant. By appropriately choosing such a function, not only can we account for models seen so far in the literature, but we can also derive novel ones
Reducing "Structure From Motion": a General Framework for Dynamic Vision - Part 1: Modeling
The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of different models and estimation techniques. We propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction.
The "natural" dynamic model, derived by the rigidity constraint and the perspective projection, is first reduced by explicitly decoupling structure (depth) from motion. Then implicit decoupling techniques are explored, which consist of imposing that some function of the unknown parameters is held constant. By appropriately choosing such a function, not only can we account for all models seen so far in the literature, but we can also derive novel ones
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