960 resultados para Mobile Robot
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In this paper the authors intend to demonstrate the utilization of remote experimentation (RE) using mobile computational devices in the Science areas of the elementary school, with the purpose to develop practices that will help in the assimilation process of the subjects taught in classroom seeking to interlink them with the daily students? activities. Allying mobility with RE we intend to minimize the space-temporal barrier giving more availability and speed in the information access. The implemented architecture utilizes technologies and freely distributed softwares with open code resources besides remote experiments developed in the Laboratory of Remote Experimentation (RExLab) of Federal University of Santa Catarina (UFSC), in Brazil, through the physical computation platform of the ?open hardware of construction of our own. The utilization of open code computational tools and the integration of hardware to the 3D virtual worlds, accessible through mobile devices, give to the project an innovative face with a high potential for reproducibility and reusability.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.
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This paper describes how to extend the access to remote experiments from mobile devices, aiming to better engage digital native students who expect a more interactive and ubiquitous access mode. The extension is based on features of HTML5 and the jQuery Mobile framework, which allow accessing the experiments from different operating systems via the browser or native applications. As a result, users have a richer interaction mode with the experiments, which includes access from simple hand-held devices such as smartphones and PDAs. Extending the access to remote experiments, from simple devices, enables its use in other educational stages, such as high schools, where teachers struggle to engage students in STEM learning. By enabling students to use their everyday "technological companions", e.g. cellular phones, to access remote experiments, we seek to increase the educational value of this technology-enhanced learning resource.
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In this article the authors describe the application development RExMobile and the importance of remote experimentation via mobile devices, especially smartphones simple, beyond the space provided for this application in education. The article deals the creation, software and hardware that provide an interactive and dynamic way to attract more students to use these experiments remote, serving as support to teachers to science teaching from its initial series. The ease and availability of smartphones, even these students of basic education, permits the reach of new users and in different places. Thus, the practice of remote experimentation in mobile devices enables new spaces for access and interaction. Are used for developing software free or low cost, HTML5 and jQuery Mobile framework, that enable the creation of pages compatible with different mobile operating systems such as iOS, Android, Windows Phone, some Symbian, among others. Also are demonstrated patterns layouts that allow greater accessibility.
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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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This paper studies the performance of integer and fractional order controllers in a hexapod robot with joints at the legs having viscous friction and flexibility. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. The controller performance is analised through the Nyquist stability criterion. A set of model-based experiments reveals the influence of the different controller implementations upon the proposed metrics.
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Concepts like E-learning and M-learning are changing the traditional learning place. No longer restricted to well-defined physical places, education on Automation and other Engineering areas is entering the so-called ubiquitous learning place, where even the more practical knowledge (acquired at lab classes) is now moving into, due to emergent concepts such as Remote Experimentation or Mobile Experimentation. While Remote Experimentation is traditionally regarded as the remote access to real-world experiments through a simple web browser running on a PC connected to the Internet, Mobile Experimentation may be seen as the access to those same (or others) experiments, through mobile devices, used in M-learning contexts. These two distinct client types (PCs versus mobile devices) pose specific requirements for the remote lab infrastructure, namely the ability to tune the experiment interface according to the characteristics (e.g. display size) of the accessing device. This paper addresses those requirements, namely by proposing a new architecture for the remote lab infrastructure able to accommodate both Remote and Mobile Experimentation scenarios.
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As the variety of mobile devices connected to the Internet growts there is a correponding increase in the need to deliver content tailored to their heterogeneous characteristics. At the same time, we watch to the increase of e-learning in universities through the adoption of electronic platforms and standards. Not surprisingly, the concept of mLearning (Mobile Learning) appeared in recent years decreasing the limitation of learning location with the mobility of general portable devices. However, this large number and variety of Web-enabled devices poses several challenges for Web content creators who want to automatic get the delivery context and adapt the content to the client mobile devices. In this paper we analyze several approaches to defining delivery context and present an architecture for deliver uniform mLearning content to mobile devices denominated eduMCA - Educational Mobile Content Adaptation. With the eduMCA system the Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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Com o envelhecimento da população, as preocupações com a garantia do seu bem-estar aumentam criando a necessidade de desenvolver ferramentas que permitam monitorizar em permanência este sector da população. A utilização de smartphones pelos mais velhos pode ser crucial no seu bem-estar e na sua autonomia contribuindo para a recolha de informação importante já que estes estão muitas vezes equipados com sensores que podem dar indicações preciosas ao cuidador sobre o estado atual do paciente. Os sensores podem fornecer dados sobre a atividade física do paciente, bem como detetar quedas ou calcular a sua posição, com a ajuda do acelerómetro, do giroscópio e do sensor de campo magnético. No entanto, funcionalidades como essas requerem, obrigatoriamente, uma frequência de amostragem mínima por parte dos sensores que permita a implementação de algoritmos, que determinarão esses parâmetros da forma mais exata possível. Dado que nem sempre os pacientes se fazem acompanhar do seu smartphone quando estão na sua residência, a criação de ambientes de AAL (Ambient Assisted Living) com recurso a dispositivos externos que podem ser “vestidos” pelos pacientes pode também ser uma solução adequada. Estes contêm normalmente os mesmos sensores que os smartphones e comunicam com estes através de tecnologias sem fios, como é o caso do Bluetooth Low Energy. Neste trabalho, avaliou-se a possibilidade de alteração da frequência dos sensores em diferentes sistemas operativos, tendo sido efectuadas modificações nas instalações por defeito de alguns sistemas operativos abertos. Com o objectivo de permitir a criação de uma solução de AAL com recurso a um dispositivo externo implementaram-se serviços e perfis num dispositivo externo, o SensorTag.
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Os sistemas de perceção existentes nos robôs autónomos, hoje em dia, são bastante complexos. A informação dos vários sensores, existentes em diferentes partes do robôs, necessitam de estar relacionados entre si face ao referencial do robô ou do mundo. Para isso, o conhecimento da atitude (posição e rotação) entre os referenciais dos sensores e o referencial do robô é um fator critico para o desempenho do mesmo. O processo de calibração dessas posições e translações é chamado calibração dos parâmetros extrínsecos. Esta dissertação propõe o desenvolvimento de um método de calibração autónomo para robôs como câmaras direcionais, como é o caso dos robôs da equipa ISePorto. A solução proposta consiste na aquisição de dados da visão, giroscópio e odometria durante uma manobra efetuada pelo robô em torno de um alvo com um padrão conhecido. Esta informação é então processada em conjunto através de um Extended Kalman Filter (EKF) onde são estimados necessários para relacionar os sensores existentes no robô em relação ao referencial do mesmo. Esta solução foi avaliada com recurso a vários testes e os resultados obtidos foram bastante similares aos obtidos pelo método manual, anteriormente utilizado, com um aumento significativo em rapidez e consistência.