710 research outputs found

    Improved vision based pose estimation for industrial robots via sparse regression

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    In this work amonocular machine vision based pose estimation system is developed for industrial robots and the accuracy of the estimated pose is im-proved via sparse regression. The proposed sparse regressionbased methodis usedimprove the accuracy obtained from the Levenberg-Marquardt (LM) based pose estimation algorithmduring the trajectory tracking of an industrial robot’s end effector. The proposed method utilizes a set of basis functions to sparsely identify the nonlinear relationship between the estimated pose and the true pose provided by a laser tracker.Moreover,a camera target was designed and fitted with fiducial markers,andto prevent ambiguities in pose estimation, the markers are placed in such a way to guarantee the detection of at least two distinct nonparallel markers from a single camera within ± 90° in all directions of the cam-era’s view. The effectiveness of the proposed method is validated by an experi-mental study performed using a KUKA KR240 R2900 ultra robot while follow-ing sixteen distinct trajectories based on ISO 9238. The obtained results show that the proposed method provides parsimonious models which improve the pose estimation accuracy and precision of the vision based system during trajectory tracking of industrial robots' end effector

    Closed-loop separation control over a sharp edge ramp using Genetic Programming

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    We experimentally perform open and closed-loop control of a separating turbulent boundary layer downstream from a sharp edge ramp. The turbulent boundary layer just above the separation point has a Reynolds number Reξ≈3 500Re_{\theta}\approx 3\,500 based on momentum thickness. The goal of the control is to mitigate separation and early re-attachment. The forcing employs a spanwise array of active vortex generators. The flow state is monitored with skin-friction sensors downstream of the actuators. The feedback control law is obtained using model-free genetic programming control (GPC) (Gautier et al. 2015). The resulting flow is assessed using the momentum coefficient, pressure distribution and skin friction over the ramp and stereo PIV. The PIV yields vector field statistics, e.g. shear layer growth, the backflow area and vortex region. GPC is benchmarked against the best periodic forcing. While open-loop control achieves separation reduction by locking-on the shedding mode, GPC gives rise to similar benefits by accelerating the shear layer growth. Moreover, GPC uses less actuation energy.Comment: 24 pages, 24 figures, submitted to Experiments in Fluid

    Molecular and morphometric variation in European populations of the articulate brachiopod <i>Terebeatulina retusa</i>

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    Molecular and morphometric variation within and between population samples of the articulate brachiopod &lt;i&gt;Terebratulina&lt;/i&gt; spp., collected in 1985-1987 from a Norwegian fjord, sea lochs and costal sites in western Scotland, the southern English Channel (Brittany) and the western Mediterranean, were measured by the analysis of variation in the lengths of mitochondrial DNA (mtDNA) fragments produced by digestion with nine restriction endonucleases and by multivariate statistical analysis of six selected morphometric parameters. Nucleotide difference within each population sample was high. Nucleotide difference between population samples from the Scottish sites, both those that are tidally contiguous and those that appear to be geographically isolated, were not significantly different from zero. Nucleotide differences between the populations samples from Norway, Brittany, Scotland and the western Mediterranean were also very low. Morphometric analysis confirmed the absence of substantial differentiation

    Harnessing energies, resolving tensions: acknowledging a dual heritage for qualitative evidence synthesis

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    Qualitative evidence synthesis (QES) encompasses more than 20 methods for synthesizing qualitative accounts of research phenomena documenting real-life contexts. However, tensions frequently arise from the different heritages that shape QES methodology: namely, systematic reviews of effectiveness and primary qualitative research. Methodological innovations either derive from each heritage or are stimulated when both are in juxtaposition; it is important to broker a rapprochement. This article draws on practical experience from a range of syntheses and methodological development work conducted with the Cochrane Qualitative and Implementation Methods Group. The legacy of both heritages is briefly characterized. Three stages of the QES process offer exemplars: searching/sampling, quality assessment, and data synthesis. Rather than an antagonistic clash of research paradigms, this dual heritage offers an opportunity to harness the collective energies of both paradigms. Future methodological research is needed to identify further applications by which this dual heritage might be optimally harnessed

    The effectiveness of interventions to change six health behaviours: a review of reviews

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    Background: Several World Health Organisation reports over recent years have highlighted the high incidence of chronic diseases such as diabetes, coronary heart disease and cancer. Contributory factors include unhealthy diets, alcohol and tobacco use and sedentary lifestyles. This paper reports the findings of a review of reviews of behavioural change interventions to reduce unhealthy behaviours or promote healthy behaviours. We included six different health-related behaviours in the review: healthy eating, physical exercise, smoking, alcohol misuse, sexual risk taking (in young people) and illicit drug use. We excluded reviews which focussed on pharmacological treatments or those which required intensive treatments (e. g. for drug or alcohol dependency). Methods: The Cochrane Library, Database of Abstracts of Reviews of Effectiveness (DARE) and several Ovid databases were searched for systematic reviews of interventions for the six behaviours (updated search 2008). Two reviewers applied the inclusion criteria, extracted data and assessed the quality of the reviews. The results were discussed in a narrative synthesis. Results: We included 103 reviews published between 1995 and 2008. The focus of interventions varied, but those targeting specific individuals were generally designed to change an existing behaviour (e. g. cigarette smoking, alcohol misuse), whilst those aimed at the general population or groups such as school children were designed to promote positive behaviours (e. g. healthy eating). Almost 50% (n = 48) of the reviews focussed on smoking (either prevention or cessation). Interventions that were most effective across a range of health behaviours included physician advice or individual counselling, and workplace- and school-based activities. Mass media campaigns and legislative interventions also showed small to moderate effects in changing health behaviours. Generally, the evidence related to short-term effects rather than sustained/longer-term impact and there was a relative lack of evidence on how best to address inequalities. Conclusions: Despite limitations of the review of reviews approach, it is encouraging that there are interventions that are effective in achieving behavioural change. Further emphasis in both primary studies and secondary analysis (e.g. systematic reviews) should be placed on assessing the differential effectiveness of interventions across different population subgroups to ensure that health inequalities are addressed.</p

    Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks

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    Generating realistic 3D faces is of high importance for computer graphics and computer vision applications. Generally, research on 3D face generation revolves around linear statistical models of the facial surface. Nevertheless, these models cannot represent faithfully either the facial texture or the normals of the face, which are very crucial for photo-realistic face synthesis. Recently, it was demonstrated that Generative Adversarial Networks (GANs) can be used for generating high-quality textures of faces. Nevertheless, the generation process either omits the geometry and normals, or independent processes are used to produce 3D shape information. In this paper, we present the first methodology that generates high-quality texture, shape, and normals jointly, which can be used for photo-realistic synthesis. To do so, we propose a novel GAN that can generate data from different modalities while exploiting their correlations. Furthermore, we demonstrate how we can condition the generation on the expression and create faces with various facial expressions. The qualitative results shown in this paper are compressed due to size limitations, full-resolution results and the accompanying video can be found in the supplementary documents. The code and models are available at the project page: https://github.com/barisgecer/TBGAN.Comment: Check project page: https://github.com/barisgecer/TBGAN for the full resolution results and the accompanying vide

    A statistical learning strategy for closed-loop control of fluid flows

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    This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system’s dynamics. A control strategy is then learned using reinforcement learning once rewards relevant with respect to the control objective are identified. This method is designed for experimental configurations, requiring no computations nor prior knowledge of the system, and enjoys intrinsic robustness. It is illustrated on two systems: the control of the transitions of a Lorenz’63 dynamical system, and the control of the drag of a cylinder flow. The method is shown to perform well
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