837 resultados para INTELLIGENT ROBOTS GRIPPER
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Tesis (Maestro en Ciencias de la Ingeniería Eléctrica con orientación en Control Automático) UANL, 2013.
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Tesis (Doctor en Ingeniería Eléctrica) UANL, 1999.
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Tesis (Doctor en Ingeniería Eléctrica) UANL, 1999.
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Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal
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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal
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Cette thèse vise à définir une nouvelle méthode d’enseignement pour les systèmes tutoriels intelligents dans le but d’améliorer l’acquisition des connaissances. L’apprentissage est un phénomène complexe faisant intervenir des mécanismes émotionnels et cognitifs de nature consciente et inconsciente. Nous nous intéressons à mieux comprendre les mécanismes inconscients du raisonnement lors de l’acquisition des connaissances. L’importance de ces processus inconscients pour le raisonnement est bien documentée en neurosciences, mais demeure encore largement inexplorée dans notre domaine de recherche. Dans cette thèse, nous proposons la mise en place d’une nouvelle approche pédagogique dans le domaine de l’éducation implémentant une taxonomie neuroscientifique de la perception humaine. Nous montrons que cette nouvelle approche agit sur le raisonnement et, à tour de rôle, améliore l’apprentissage général et l’induction de la connaissance dans un environnement de résolution de problème. Dans une première partie, nous présentons l’implémentation de notre nouvelle méthode dans un système tutoriel visant à améliorer le raisonnement pour un meilleur apprentissage. De plus, compte tenu de l’importance des mécanismes émotionnels dans l’apprentissage, nous avons également procédé dans cette partie à la mesure des émotions par des capteurs physiologiques. L’efficacité de notre méthode pour l’apprentissage et son impact positif observé sur les émotions a été validée sur trente et un participants. Dans une seconde partie, nous allons plus loin dans notre recherche en adaptant notre méthode visant à améliorer le raisonnement pour une meilleure induction de la connaissance. L’induction est un type de raisonnement qui permet de construire des règles générales à partir d’exemples spécifiques ou de faits particuliers. Afin de mieux comprendre l’impact de notre méthode sur les processus cognitifs impliqués dans ce type de raisonnement, nous avons eu recours à des capteurs cérébraux pour mesurer l’activité du cerveau des utilisateurs. La validation de notre approche réalisée sur quarante-trois volontaires montre l’efficacité de notre méthode pour l’induction de la connaissance et la viabilité de mesurer le raisonnement par des mesures cérébrales suite à l’application appropriée d’algorithmes de traitement de signal. Suite à ces deux parties, nous clorons la thèse par une discussion applicative en décrivant la mise en place d’un nouveau système tutoriel intelligent intégrant les résultats de nos travaux.
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School of Management Studies, Cochin University of Science and Technology
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Màster Oficial en Gestió del Patrimoni Cultural
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The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India
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A new localization approach to increase the navigational capabilities and object manipulation of autonomous mobile robots, based on an encoded infrared sheet of light beacon system, which provides position errors smaller than 0.02m is presented in this paper. To achieve this minimal position error, a resolution enhancement technique has been developed by utilising an inbuilt odometric/optical flow sensor information. This system respects strong low cost constraints by using an innovative assembly for the digitally encoded infrared transmitter. For better guidance of mobile robot vehicles, an online traffic signalling capability is also incorporated. Other added features are its less computational complexity and online localization capability all these without any estimation uncertainty. The constructional details, experimental results and computational methodologies of the system are also described
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Association rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation.
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In early stages of architectural design, as in other design domains, the language used is often very abstract. In architectural design, for example, architects and their clients use experiential terms such as "private" or "open" to describe spaces. If we are to build programs that can help designers during this early-stage design, we must give those programs the capability to deal with concepts on the level of such abstractions. The work reported in this thesis sought to do that, focusing on two key questions: How are abstract terms such as "private" and "open" translated into physical form? How might one build a tool to assist designers with this process? The Architect's Collaborator (TAC) was built to explore these issues. It is a design assistant that supports iterative design refinement, and that represents and reasons about how experiential qualities are manifested in physical form. Given a starting design and a set of design goals, TAC explores the space of possible designs in search of solutions that satisfy the goals. It employs a strategy we've called dependency-directed redesign: it evaluates a design with respect to a set of goals, then uses an explanation of the evaluation to guide proposal and refinement of repair suggestions; it then carries out the repair suggestions to create new designs. A series of experiments was run to study TAC's behavior. Issues of control structure, goal set size, goal order, and modification operator capabilities were explored. In addition, TAC's use as a design assistant was studied in an experiment using a house in the process of being redesigned. TAC's use as an analysis tool was studied in an experiment using Frank Lloyd Wright's Prairie houses.
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Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, regarding (1) dissemination of information from informed to uninformed traders, and (2) aggregation of information spread over different traders.
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Hypermedia systems based on the Web for open distance education are becoming increasingly popular as tools for user-driven access learning information. Adaptive hypermedia is a new direction in research within the area of user-adaptive systems, to increase its functionality by making it personalized [Eklu 961. This paper sketches a general agents architecture to include navigational adaptability and user-friendly processes which would guide and accompany the student during hislher learning on the PLAN-G hypermedia system (New Generation Telematics Platform to Support Open and Distance Learning), with the aid of computer networks and specifically WWW technology [Marz 98-1] [Marz 98-2]. The PLAN-G actual prototype is successfully used with some informatics courses (the current version has no agents yet). The propased multi-agent system, contains two different types of adaptive autonomous software agents: Personal Digital Agents {Interface), to interacl directly with the student when necessary; and Information Agents (Intermediaries), to filtrate and discover information to learn and to adapt navigation space to a specific student
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This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields