910 resultados para ROS (Robot Operating System)
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É crescente a utilização dos dispositivos móveis com ecrãs maiores e melhores, mais memória, maiores capacidades multimédia e métodos mais refinados para introduzir dados. Dispositivos que integram comunicações, acesso à internet e diversos tipos de sensores possibilitarão, seguramente, abordagens inovadoras e criativas em atividades pedagógicas, em contraste com as utilizações atuais nos computadores pessoais. A análise das aplicações que atualmente integram os módulos do Moodle nos dispositivos móveis mostra que existe ainda um longo caminho a percorrer. As aplicações existentes têm, quase na sua totalidade, como objetivo adaptar o interface aos dispositivos móveis, o que é apenas o primeiro passo no sentido de aproveitar todas as potencialidades destes dispositivos. É, pois, possível imaginar um futuro próximo, onde as potencialidades dos dispositivos móveis darão origem a aplicações com um enorme potencial de aprendizagem, que advém do facto de os estudantes encontrarem conexões entre as suas vidas e a sua educação, através da realização de atividades em contexto no dispositivo móvel, sempre omnipresente. Com este trabalho de investigação e desenvolvimento pretende-se: a) avaliar o estado da arte do mobile learning, na área dos Learning Management System (LMS); b) refletir sobre as funcionalidades que deve oferecer uma aplicação para dispositivos móveis, com enfoque no sistema operativo Android, que permita a gestão e atualização dos fóruns e ficheiros do Moodle; c) conceber e produzir a referida aplicação, de acordo com as especificações consideradas relevantes; d) avaliar o seu impacto educativo e funcional. É demonstrado neste estudo que o recurso a dispositivos móveis potencia a aprendizagem baseada em LMS (Learning Management System), identificando-se as vantagens da sua utilização. São também apresentadas as funcionalidades da aplicação Mais(f), desenvolvida no âmbito da investigação, a avaliação da mesma pelos participantes no estudo, bem como as perspectivas futuras de utilização da aplicação Mais(f).
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Geociências, 2016.
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Cada vez mais, se torna necessário, apresentar, transpor e adequar as Novas Tecnologias ao ambiente de aprendizagem na sala de aula, interligando não só as Áreas Curriculares Não Disciplinares (ACND) como as Áreas Curriculares Disciplinares (ACD) a um trabalho colaborativo. Por conseguinte, o objetivo deste projeto de investigação é aplicar um projeto de aprendizagem colaborativa denominado “Triângulo das Histórias”, utilizando como instrumento de partilha um blogue na internet, e avaliar o tipo de aceitação que a sua aplicação gerou. A aplicação do projeto em contexto educativo visará uma interação entre a comunidade educativa, possibilitando assim, a experimentação de comunidades virtuais de comunicação e de colaboração escolar. Para complementar este estudo pretende-se também perceber os hábitos de utilização da Internet dos alunos envolvidos no projeto. A amostra utilizada para este estudo foi um conjunto de dezoito alunos dos 1.º e 2.º Ciclos do Ensino Básico, com idades compreendidas entre os 6 e os 12 anos de idade, dos regimes público, cooperativo e particular, repartidos por três escolas distintas, com meios socioeconómicos também diferentes. Para a recolha dos dados foi realizado um inquérito aos alunos envolvidos no projeto e realizadas observações sobre as suas interações e comportamentos. Os dados extraídos dos inquéritos foram apresentados sob a forma de gráfico. A implementação deste projeto permitiu perceber que os alunos foram recetivos a esta nova abordagem de realização de trabalho de grupo colaborativo recorrendo às comunidades virtuais. A criação de uma história associando três escolas distintas permitiu que os alunos, para além de terem de elaborar um texto de forma coletiva, tivessem acesso a novas ferramentas tanto da internet como do sistema operativo, tornando-se, desta forma, um bom complemento de aprendizagem.
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Dissertação de mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2011
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Current industry proposals for Hardware Transactional Memory (HTM) focus on best-effort solutions (BE-HTM) where hardware limits are imposed on transactions. These designs may show a significant performance degradation due to high contention scenarios and different hardware and operating system limitations that abort transactions, e.g. cache overflows, hardware and software exceptions, etc. To deal with these events and to ensure forward progress, BE-HTM systems usually provide a software fallback path to execute a lock-based version of the code. In this paper, we propose a hardware implementation of an irrevocability mechanism as an alternative to the software fallback path to gain insight into the hardware improvements that could enhance the execution of such a fallback. Our mechanism anticipates the abort that causes the transaction serialization, and stalls other transactions in the system so that transactional work loss is mini- mized. In addition, we evaluate the main software fallback path approaches and propose the use of ticket locks that hold precise information of the number of transactions waiting to enter the fallback. Thus, the separation of transactional and fallback execution can be achieved in a precise manner. The evaluation is carried out using the Simics/GEMS simulator and the complete range of STAMP transactional suite benchmarks. We obtain significant performance benefits of around twice the speedup and an abort reduction of 50% over the software fallback path for a number of benchmarks.
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Se han desarrollado varios modelos prometedores para la captura digital de datos de movilidad, que pueden ser aplicados en la planificación urbana, de transporte y de ordenamiento territorial. Por ello el objetivo de este trabajo es desarrollar una metodología que recolecte información de movilidad con la cual se generen matrices Origen-Destino (OD) y de tiempos de viajes, además que identifique puntos de interés, modos y rutas frecuentes de viaje mediante el desarrollo e implementación de una aplicación para dispositivos móviles Android. Metodología: Se produjo una aplicación para dispositivos móviles con sistema operativo Android, en base a modelos existentes. Esta aplicación obtuvo datos de movilidad a partir de los sensores de localización incorporados en los móviles (GPS), para su posterior migración a una base de datos en la nube y consiguiente post proceso con herramientas de análisis como KNIME, Python y QuantumGis. La aplicación fue probada por 68 estudiantes voluntarios de la Universidad de Cuenca, durante 14 días del mes de enero de 2016. Resultados: Con la información completa de 44 participantes se obtuvieron matrices OD y de tiempos de viajes para diferentes períodos del día, las cuales permitieron identificar variaciones de interacción entre zonas, variaciones de número y tiempo de viajes. Fueron reconocidos también modos de transporte como caminata, bicicleta y motorizados para una sub muestra (n=6). Se detectaron los POIs Residencia (91%), Trabajo/Estudio (74%) y puntos intermedios (20% del total de POIs) y se logró observar comportamientos de movilidad atípico. Finalmente se compararon las rutas más frecuentadas por los usuarios con las rutas óptimas teóricas calculadas, encontrando que el 63.6% de los usuarios coincidían con el recorrido de estas últimas. Conclusiones: El método planteado presenta coherencia con trabajos previos, mostrando niveles de confianza equiparables. El mayor reto es la implementación masiva del modelo creado para la recolección de datos útiles para planes de movilidad.
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In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.
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The Division of Professional and Occupational Licensing is an administrative unit within the Department of Labor, Licensing, and Regulation that provides support to 40 professional and occupational regulatory boards. All board members need documents to review during the meeting. Some boards use a fleet of dated laptops during the meetings to give board members the meeting materials in PDF format; however many of boards still print the meeting materials and put them into binders. .In today's age, there has to be a more efficient way to conduct meetings without all of the paper. This paper explores alternatives to paper and laptops for use at these meetings. It was concluded that a tablet with a Windows Operating System would be the best way to go.
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The presented Thesis describes the design of RF-energy harvesting systems with applications on different environments, from the biomedical side to the industrial one, tackling the common thread problem which is the design of complete energy autonomous tags each of them with its dedicated purpose. This Thesis gathers a work of three years in the field of energy harvesting system design, a combination of full-wave electromagnetic designs to optimize not only the antenna performance but also to fulfill the requirements given by each case study such as dimensions, insensitivity from the surrounding environment, flexibility and compliance with regulations. The research activity has been based on the development of highly-demanded ideas and real-case necessities which are in line with the environment in which modern IoT applications can really make a positive contribution. The Thesis is organized as follows: the first application, described in Chapter 2, regards the design and experimental validations of a rotation-insensitive WPT system for implantable devices. Chapter 3 presents the design of a wearable energy autonomous detector to identify the presence of ethanol on the body surface. Chapter 4 describes investigations in the use of Bessel Beam launchers for creating a highly-focused energy harvesting link for wearable applications. Reduced dimensions, high focusing and decoupling from the human body are the key points to be addressed during the full-wave design and nonlinear optimization of the receiver antenna. Finally, Chapter 5 presents an energy autonomous system exploiting LoRa (Long Range) nodes for tracking trailers in industrial plants. The novelty behind this design lies on the aim of obtaining a perfectly scalable system that exploits not only EH basic operating system but embeds a seamless solution for collecting a certain amount of power that varies with respect the received power level on the antenna, without the need of additional off-the-shelf components.
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The industrial context is changing rapidly due to advancements in technology fueled by the Internet and Information Technology. The fourth industrial revolution counts integration, flexibility, and optimization as its fundamental pillars, and, in this context, Human-Robot Collaboration has become a crucial factor for manufacturing sustainability in Europe. Collaborative robots are appealing to many companies due to their low installation and running costs and high degree of flexibility, making them ideal for reshoring production facilities with a short return on investment. The ROSSINI European project aims to implement a true Human-Robot Collaboration by designing, developing, and demonstrating a modular and scalable platform for integrating human-centred robotic technologies in industrial production environments. The project focuses on safety concerns related to introducing a cobot in a shared working area and aims to lay the groundwork for a new working paradigm at the industrial level. The need for a software architecture suitable to the robotic platform employed in one of three use cases selected to deploy and test the new technology was the main trigger of this Thesis. The chosen application consists of the automatic loading and unloading of raw-material reels to an automatic packaging machine through an Autonomous Mobile Robot composed of an Autonomous Guided Vehicle, two collaborative manipulators, and an eye-on-hand vision system for performing tasks in a partially unstructured environment. The results obtained during the ROSSINI use case development were later used in the SENECA project, which addresses the need for robot-driven automatic cleaning of pharmaceutical bins in a very specific industrial context. The inherent versatility of mobile collaborative robots is evident from their deployment in the two projects with few hardware and software adjustments. The positive impact of Human-Robot Collaboration on diverse production lines is a motivation for future investments in research on this increasingly popular field by the industry.
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In the recent decades, robotics has become firmly embedded in areas such as education, teaching, medicine, psychology and many others. We focus here on social robotics; social robots are designed to interact with people in a natural and interpersonal way, often to achieve positive results in different applications. To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like intelligence. The rapid expansion of social robotics and the existence of various kinds of robots on the market have allowed research groups to carry out multiple experiments. The experiments carried out have led to the collections of various kinds of data, which can be used or processed for psychological studies, and studies in other fields. However, there are no tools available in which data can be stored, processed and shared with other research groups. This thesis proposes the design and implementation of visual tool for organizing dataflows in Human Robot Interaction (HRI).
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This work discusses the use of optical flow to generate the sensorial information a mobile robot needs to react to the presence of obstacles when navigating in a non-structured environment. A sensing system based on optical flow and time-to-collision calculation is here proposed and experimented, which accomplishes two important paradigms. The first one is that all computations are performed onboard the robot, in spite of the limited computational capability available. The second one is that the algorithms for optical flow and time-to-collision calculations are fast enough to give the mobile robot the capability of reacting to any environmental change in real-time. Results of real experiments in which the sensing system here proposed is used as the only source of sensorial data to guide a mobile robot to avoid obstacles while wandering around are presented, and the analysis of such results allows validating the proposed sensing system.
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Dissertation presented at Faculty of Sciences and Technology of the New University of Lisbon to attain the Master degree in Electrical and Computer Science Engineering
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Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.
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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