3,587 research outputs found

    Understanding of Object Manipulation Actions Using Human Multi-Modal Sensory Data

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    Object manipulation actions represent an important share of the Activities of Daily Living (ADLs). In this work, we study how to enable service robots to use human multi-modal data to understand object manipulation actions, and how they can recognize such actions when humans perform them during human-robot collaboration tasks. The multi-modal data in this study consists of videos, hand motion data, applied forces as represented by the pressure patterns on the hand, and measurements of the bending of the fingers, collected as human subjects performed manipulation actions. We investigate two different approaches. In the first one, we show that multi-modal signal (motion, finger bending and hand pressure) generated by the action can be decomposed into a set of primitives that can be seen as its building blocks. These primitives are used to define 24 multi-modal primitive features. The primitive features can in turn be used as an abstract representation of the multi-modal signal and employed for action recognition. In the latter approach, the visual features are extracted from the data using a pre-trained image classification deep convolutional neural network. The visual features are subsequently used to train the classifier. We also investigate whether adding data from other modalities produces a statistically significant improvement in the classifier performance. We show that both approaches produce a comparable performance. This implies that image-based methods can successfully recognize human actions during human-robot collaboration. On the other hand, in order to provide training data for the robot so it can learn how to perform object manipulation actions, multi-modal data provides a better alternative

    On the use of simulated experiments in designing tests for material characterization from full-field measurements

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    The present paper deals with the use of simulated experiments to improve the design of an actual mechanical test. The analysis focused on the identification of the orthotropic properties of composites using the unnotched Iosipescu test and a full-field optical technique, the grid method. The experimental test was reproduced numerically by finite element analysis and the recording of deformed grey level images by a CCD camera was simulated trying to take into account the most significant parameters that can play a role during an actual test, e.g. the noise, the failure of the specimen, the size of the grid printed on the surface, etc. The grid method then was applied to the generated synthetic images in order to extract the displacement and strain fields and the Virtual Fields Method was finally used to identify the material properties and a cost function was devised to evaluate the error in the identification. The developed procedure was used to study different features of the test such as the aspect ratio and the fibre orientation of the specimen, the use of smoothing functions in the strain reconstruction from noisy data, the influence of missing data on the identification. Four different composite materials were considered and, for each of them, a set of optimized design variables was found by minimization of the cost function

    The 64 Mpixel wide field imager for the Wendelstein 2m Telescope: Design and Calibration

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    The Wendelstein Observatory of Ludwig Maximilians University of Munich has recently been upgraded with a modern 2m robotic telescope. One Nasmyth port of the telescope has been equipped with a wide-field corrector which preserves the excellent image quality (< 0.8" median seeing) of the site (Hopp et al. 2008) over a field of view of 0.7 degrees diameter. The available field is imaged by an optical imager (WWFI, the Wendelstein Wide Field Imager) built around a customized 2 Ɨ\times 2 mosaic of 4k Ɨ\times 4k 15 \mu m e2v CCDs from Spectral Instruments. This paper provides an overview of the design and the WWFI's performance. We summarize the system mechanics (including a structural analysis), the electronics (and its electromagnetic interference (EMI) protection) and the control software. We discuss in detail detector system parameters, i.e. gain and readout noise, quantum efficiency as well as charge transfer efficiency (CTE) and persistent charges. First on sky tests yield overall good predictability of system throughput based on lab measurements.Comment: 38 pages 19 Figures To be published in Springer Experimental Astronom
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