913 resultados para GPS positioning


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Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

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In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

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El trabajo no ha sido publicado. En el CD adjunto se encuentran las presentaciones realizadas. Resumen basado en ficha elaborada por los autores

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Resumen tomado de la publicación. Monográfico con el título: interdisciplinariedad y educación física

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Este proyecto de innovación educativa se presentó en el Congreso Internacional de Innovación en la Educación celebrado en Valladolid los dias 26, 27 y 28 de abril de 2005

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Este proyecto ha sido desarrollado en el Departamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemática de la Universidad de Valladolid, y han contribuido a su realización cuatro profesores del citado departamento. El objetivo principal de este proyecto ha sido desarrollar un programa informático que permita la navegación terrestre mediante el Sistema de Posicionamiento Global por Satélites (GPS). Concretamente, se ha aplicado para que permita la navegación terrestre en los alrededores de la Escuela Técnica Superior de Ingenieros de Telecomunicación de la Universidad de Valladold. Para ello, se ha desarrollado un programa software en el entorno de programación Visual C++ . Esta aplicación dispone de un interface gráfico para el tratamiento de los datos recogidos con una tarjeta receptora GPS Microtraker, que se utiliza para adquirir los datos emitidos por los satélites y calcular los diferentes parámetros dados por este sistema. La aplicación elaborada sirve para potenciar la eficacia de las prácticas y por ello se ha adaptado para incorporarla a las prácticas relativas al sistema GPS, que se llevan a cabo en la asignatura optativa de segundo ciclo : Sistemas de telecomunicación III que se imparte en la titulación de Ingeniería de la Telecomunicación. Como resultado del proyecto tenemos la aplicación informática desarrollada que permite la navegación terrestre mediante GPS y un manual de usuario para su utilización, que en la actualidad no está publicado.

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Se contribuye a la difusi??n del que se considera que debe ser el ???libro de cabecera??? de los ense??antes de lenguas, ya que varios a??os despu??s de su publicaci??n sigue teniendo la misma o mayor vigencia para cumplir sus dos objetivos principales: fomentar la reflexi??n sobre qu?? hacemos realmente cuando nos comunicamos unos con otros, cu??les de estas capacidades tenemos que aprender, c??mo establecemos nuestros objetivos y evaluamos nuestro progreso, c??mo se realiza el aprendizaje de una lengua y qu?? podemos hacer para aprender mejor; y 2) facilitar que los profesionales se comuniquen entre s?? y puedan informar a su alumnado sobre los objetivos y c??mo alcanzarlos.

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We examine the motion of the ground surface on the Soufriere Hills Volcano, Montserrat between 1998 and 2000 using radar interferometry (InSAR). To minimise the effects of variable atmospheric water vapour on the InSAR measurements we use independently-derived measurements of the radar path delay from six continuous GPS receivers. The surfaces providing a measurable inter-ferometric signal are those on pyroclastic flow deposits, mainly emplaced in 1997. Three types of surface motion can be discriminated. Firstly, the surfaces of thick, valley-filling deposits subsided at rates of 150-120 mm/year in the year after emplacement to 50-30 mm/year two years later. This must be due to contraction and settling effects during cooling. The second type is the near-field motion localised within about one kilometre of the dome. Both subsidence and uplift events are seen and though the former could be due to surface gravitational effects, the latter may reflect shallow (< 1 km) pressurisation effects within the conduit/dome. Far-field motions of the surface away from the deeply buried valleys are interpreted as crustal strains. Because the flux of magma to the surface stopped from March 1998 to November 1999 and then resumed from November 1999 through 2000, we use InSAR data from these two periods to test the crustal strain behaviour of three models of magma supply: open, depleting and unbalanced. The InSAR observations of strain gradients of 75-80 mm/year/krn uplift during the period of quiescence on the western side of the volcano are consistent with an unbalanced model in which magma supply into a crustal magma chamber continues during quiescence, raising chamber pressure that is then released upon resumption of effusion. GPS motion vectors agree qualitatively with the InSAR displacements but are of smaller magnitude. The discrepancy may be due to inaccurate compensation for atmospheric delays in the InSAR data. (c) 2005 Elsevier B.V. All rights reserved.

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This paper presents a study on applying an integrated Global Position System (GPS) and Geographacial Information System (GIS) technology to the reduction of construction waste. During the study, a prototype study is developed from automatic data capture system such as the barcoding system for construction material and equipment (M&E) management onsite, whilst the integrated GPS and GIS technology is combined to the M&E system based on the Wide Area Network (WAN). Then, a case study is conducted to demonstrate the deployment of the system. Experimental results indicate that the proposed system can minimize the amount of onsite material wastage.

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Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).

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The periodic domains formed by block copolymer melts have been heralded as potential scaffolds for arranging nanoparticles in 3d space, provided we can control the positioning of the particles. Recent experiments have located particles at the domain interfaces by grafting mixed brushes to their surfaces. Here the underlying mechanism, which involves the transformation into Janus particles, is investigated with self-consistent field theory using a new multi-coordinate-system algorithm.

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Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).