9 resultados para desig automation of robots

em Universidade do Minho


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Tese de Doutoramento em Tecnologias e Sistemas de Informação

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The research of stereotactic apparatus to guide surgical devices began in 1908, yet a major part of today's stereotactic neurosurgeries still rely on stereotactic frames developed almost half a century ago. Robots excel at handling spatial information, and are, thus, obvious candidates in the guidance of instrumentation along precisely planned trajectories. In this review, we introduce the concept of stereotaxy and describe a standard stereotactic neurosurgery. Neurosurgeons' expectations and demands regarding the role of robots as assistive tools are also addressed. We list the most successful robotic systems developed specifically for or capable of executing stereotactic neurosurgery. A critical review is presented for each robotic system, emphasizing the differences between them and detailing positive features and drawbacks. An analysis of the listed robotic system features is also undertaken, in the context of robotic application in stereotactic neurosurgery. Finally, we discuss the current perspective, and future directions of a robotic technology in this field. All robotic systems follow a very similar and structured workflow despite the technical differences that set them apart. No system unequivocally stands out as an absolute best. The trend of technological progress is pointing toward the development of miniaturized cost-effective solutions with more intuitive interfaces.

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With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

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Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

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IP networks are currently the major communication infrastructure used by an increasing number of applications and heterogeneous services, including voice services. In this context, the Session Initiation Protocol (SIP) is a signaling protocol widely used for controlling multimedia communication sessions such as voice or video calls over IP networks, thus performing vital functions in an extensive set of public and enter- prise solutions. However, the SIP protocol dissemination also entails some challenges, such as the complexity associated with the testing/validation processes of IMS/SIP networks. As a consequence, manual IMS/SIP testing solutions are inherently costly and time consuming tasks, being crucial to develop automated approaches in this specific area. In this perspective, this article presents an experimental approach for automated testing/validation of SIP scenarios in IMS networks. For that purpose, an automation framework is proposed allowing to replicate the configuration of SIP equipment from the pro- duction network and submit such equipment to a battery of tests in the testing network. The proposed solution allows to drastically reduce the test and validation times when compared with traditional manual approaches, also allowing to enhance testing reliability and coverage. The automation framework comprises of some freely available tools which are conveniently integrated with other specific modules implemented within the context of this work. In order to illustrate the advantages of the proposed automated framework, a real case study taken from a PT Inovação customer is presented comparing the time required to perform a manual SIP testing approach with the one time required when using the proposed auto- mated framework. The presented results clearly corroborate the advantages of using the presented framework.

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Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

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This chapter presents a general view of multibody system concept and definition by describing the main features associated with spatial systems. The mechanical components, which can be modeled as rigid or flexible, are constrained by kinematic pair of different types. Additionally, the bodies can be actuated upon by force elements and external forces due to interaction with environment. This chapter also presents some examples of application of multibody systems that can include automotive vehicles, mechanisms, robots and biomechanical systems.