Dissecção robótica da artéria torácica interna direita por esternotomia mediana

A utilização de sistemas robóticos em cirurgia cardíaca visa à diminuição do trauma operatório. A revascularização do miocárdio totalmente endoscópica, assistida por robô DaVinci (Intuitive Surgical, Sunnyvale, Califórnia) é factível e seu aprendizado deve ser realizado em etapas. O primeiro passo é o preparo da artéria torácica interna esquerda, já por via totalmente endoscópica. O caso apresentado propõe a dissecção da artéria torácica interna direita por esternotomia completa. Propõe um novo passo rumo ao procedimento completamente endoscópico, visando à diminuição de lesões decorrentes da curva de aprendizado.The use of robotic systems in cardiac surgeries aims at decreasing the surgical trauma.

Adaptive Regelung von Robotersystemen in Kontaktaufgaben

Contact Tasks of Robotic Systems, Mobile Legged Robots, Industrial Manipulators, Service Operations, Robot's Locomotion, Adaptive Control, Impedance/Force Control

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Reconeixement de veu mitjançant xarxes neuronals

La interacció home-màquina per mitjà de la veu cobreix moltes àrees d’investigació. Es destaquen entre altres, el reconeixement de la parla, la síntesis i identificació de discurs, la verificació i identificació de locutor i l’activació per veu (ordres) de sistemes robòtics. Reconèixer la parla és natural i simple per a les persones, però és un treball complex per a les màquines, pel qual existeixen diverses metodologies i tècniques, entre elles les Xarxes Neuronals. L’objectiu d’aquest treball és desenvolupar una eina en Matlab per al reconeixement i identificació de paraules pronunciades per un locutor, entre un conjunt de paraules possibles, i amb una bona fiabilitat dins d’uns marges preestablerts. El sistema és independent del locutor que pronuncia la paraula, és a dir, aquest locutor no haurà intervingut en el procés d’entrenament del sistema. S’ha dissenyat una interfície que permet l’adquisició del senyal de veu i el seu processament mitjançant xarxes neuronals i altres tècniques. Adaptant una part de control al sistema, es podria utilitzar per donar ordres a un robot com l’Alfa6Uvic o qualsevol altre dispositiu.

Reconeixement de veu mitjançant xarxes neuronals

La interacció home-màquina per mitjà de la veu cobreix moltes àrees d’investigació. Es destaquen entre altres, el reconeixement de la parla, la síntesis i identificació de discurs, la verificació i identificació de locutor i l’activació per veu (ordres) de sistemes robòtics. Reconèixer la parla és natural i simple per a les persones, però és un treball complex per a les màquines, pel qual existeixen diverses metodologies i tècniques, entre elles les Xarxes Neuronals. L’objectiu d’aquest treball és desenvolupar una eina en Matlab per al reconeixement i identificació de paraules pronunciades per un locutor, entre un conjunt de paraules possibles, i amb una bona fiabilitat dins d’uns marges preestablerts. El sistema és independent del locutor que pronuncia la paraula, és a dir, aquest locutor no haurà intervingut en el procés d’entrenament del sistema. S’ha dissenyat una interfície que permet l’adquisició del senyal de veu i el seu processament mitjançant xarxes neuronals i altres tècniques. Adaptant una part de control al sistema, es podria utilitzar per donar ordres a un robot com l’Alfa6Uvic o qualsevol altre dispositiu.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Energy and Dynamics of the solar agricultural robot "SolarSprayer"

The main objective of the present study was to design an agricultural robot, which work is based on the generation of the electricity by the solar panel. To achieve the proper operation of the robot according to the assumed working cycle the detailed design of the main equipment was made. By analysing the possible areas of implementation together with developments, the economic forecast was held. As a result a decision about possibility of such device working in agricultural sector was made and the probable topics of the further study were found out.

Design and Development of a Remotely Operated Underwater Multi-Robot Manipulator Controller

For the scientific and commercial utilization of Ocean resources, the role of intelligent underwater robotic systems are of great importance. Scientific activities like Marine Bio-technology, Hydrographic mapping, and commercial applications like Marine mining, Ocean energy, fishing, aquaculture, cable laying and pipe lining are a few utilization of ocean resources. As most of the deep undersea exploration are beyond the reachability of divers and also as the use of operator controlled and teleoperated Remotely Operated Vehicles (ROVs) and Diver Transport Vehicles (DTVs) turn out to be highly inefficient, it is essential to have a fully automated system capable providing stable control and communication links for the unstructured undersea environment.

Entwicklung der Windenergietechnik in Deutschland und der Einfluss staatlicher Förderpolitik - Technikentwicklung in den 90er Jahren zwischen Markt und Forschungsförderung

Seit gut zehn Jahren erlebt die Windenergienutzung in Deutschland einen in der Mitte der 80er Jahre nicht für möglich gehaltenen Aufschwung. Anlagenanzahl und installierte Leistung haben in diesem Zeitraum mit durchschnittlichen jährlichen Wachstumsraten von mehr als 30 Prozent zugenommen, die mittlere installierte Leistung pro neu errichteter Anlage stieg dabei um das Zehnfache und die technische Verfügbarkeit der Anlagen liegt mittlerweile bei über 98 Prozent. Mit größer werdenden Anlagen zeigt sich weiterhin ein klarer Trend zu Blattwinkel verstellbaren Konzepten, mit zunehmend drehzahlvariabler Betriebsweise. Vor dem von Vielen für die kommenden drei bis sechs Jahre prognostizierten Einstieg in die großtechnische Offshore- Windenergienutzung mit den damit verbundenen immensen technologischen und strukturellen Herausforderungen erscheint es sinnvoll, einen kritischen Blick zurückzuwerfen auf die 90er Jahre mit den ihnen zugrunde liegenden förderpolitischen Rahmenbedingungen. Dabei soll die Frage beantwortet werden, welchen konkreten Einfluss die staatlichen Forschungs- und Förderprogramme, besonders das "250 MW Wind"-Programm, auf die Entwicklung der Windenergienutzung hatten, das heißt, unter welchen Bedingungen sich bestimmte Techniklinien durchsetzten, wie der Einfluss eines geschützten Marktes durch gesetzlich garantierte Einspeisetarife auf diese Entwicklung zu bewerten ist und schließlich, welche Fehlentwicklungen möglicher Weise eingetreten sind. Dazu wird mit Hilfe von Lernkurven gezeigt, welche Kostenreduktionen insgesamt erzielt wurden, wie hoch die dazu notwendigen staatlichen Finanzmittel waren und welche Schlussfolgerungen daraus für die Zukunft abgeleitet werden können. Die Arbeit soll insgesamt dazu beitragen, die erreichten technischen Entwicklungsschritte vor dem Hintergrund der förderpolitischen Gegebenheiten besser zu verstehen, Chancen für gezielte Änderungen in der Förderpraxis zu ergreifen und Hinweise auf die Ausgestaltung von zukünftigen Forschungsprogrammen und Entwicklungsschwerpunkten im Bereich der Windenergie zu geben, um weitere Kostensenkungspotenziale auszuschöpfen. Dabei wird sich die zukünftige Schwerpunktsetzung in der programmatischen Ausrichtung der Forschung stärker auf die drei wichtigsten Anwendungsfelder für Windenergieanlagen konzentrieren müssen, die großtechnische Offshore- Anwendung, die netzgebundene, dezentrale Energieversorgung sowie auf Windenergieanlagen zur ländlichen Elektrifizierung in autonomen Versorgungssystemen für Schwellen- und Entwicklungsländer.

Modeling, Estimation, and Control of Robot-Soil Interactions

This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of robotic systems interacting with soil, our objective is parameter estimation, not excavation. To this end, we design our manipulator with a flat plate for easy modeling of interactions. By using a flat plate, we take advantage of the wealth of research on the similar problem of earth pressure on retaining walls. There are a number of existing earth pressure models. These models typically provide estimates of force which are in uncertain relation to the true force. A recent technique, known as numerical limit analysis, provides upper and lower bounds on the true force. Predictions from the numerical limit analysis technique are shown to be in good agreement with other accepted models. Experimental methods for plate insertion, soil-tool interface friction estimation, and control of applied forces on the soil are presented. In addition, a novel graphical technique for inverting the soil models is developed, which is an improvement over standard nonlinear optimization. This graphical technique utilizes the uncertainties associated with each set of force measurements to obtain all possible parameters which could have produced the measured forces. The system is tested on three cohesionless soils, two in a loose state and one in a loose and dense state. The results are compared with friction angles obtained from direct shear tests. The results highlight a number of key points. Common assumptions are made in soil modeling. Most notably, the Mohr-Coulomb failure law and perfectly plastic behavior. In the direct shear tests, a marked dependence of friction angle on the normal stress at low stresses is found. This has ramifications for any study of friction done at low stresses. In addition, gradual failures are often observed for vertical tools and tools inclined away from the direction of motion. After accounting for the change in friction angle at low stresses, the results show good agreement with the direct shear values.

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Implementação de um CRM analítico na Fundação INATEL

As soluções informáticas de Customer Relationship Management (CRM) e os sistemas de suporte à informação, designados por Business Intelligence (BI), permitem a recolha de dados e a sua transformação em informação e em conhecimento, vital para diferenciação das organizações num Mundo globalizado e em constante mudança. A construção de um Data Warehouse corporativo é fundamental para as organizações que utilizam vários sistemas operacionais de modo a ser possível a agregação da informação. A Fundação INATEL – uma fundação privada de interesse público, 100% estatal – é um exemplo deste tipo de organização. Com uma base de dados de clientes superior a 250.000, atuando em áreas tão diferentes como sejam o Turismo, a Cultura e o Desporto, sustentado em mais de 25 sistemas informáticos autónomos. A base de estudo deste trabalho é a procura de identificação dos benefícios da implementação de um CRM Analítico na Fundação INATEL. Apresentando-se assim uma metodologia para a respetiva implementação e sugestão de um modelo de dados para a obtenção de uma visão única do cliente, acessível a toda a organização, de modo a garantir a total satisfação e consequente fidelização à marca INATEL. A disponibilização desta informação irá proporcionar um posicionamento privilegiado da Fundação INATEL e terá um papel fundamental na sua sustentabilidade económica.

A Newton method for pose refinement of 3D models

Different optimization methods can be employed to optimize a numerical estimate for the match between an instantiated object model and an image. In order to take advantage of gradient-based optimization methods, perspective inversion must be used in this context. We show that convergence can be very fast by extrapolating to maximum goodness-of-fit with Newton's method. This approach is related to methods which either maximize a similar goodness-of-fit measure without use of gradient information, or else minimize distances between projected model lines and image features. Newton's method combines the accuracy of the former approach with the speed of convergence of the latter.

A review and implementation of swarm pattern formation and transformation models

Purpose: The purpose of this paper is to address a classic problem – pattern formation identified by researchers in the area of swarm robotic systems – and is also motivated by the need for mathematical foundations in swarm systems. Design/methodology/approach: The work is separated out as inspirations, applications, definitions, challenges and classifications of pattern formation in swarm systems based on recent literature. Further, the work proposes a mathematical model for swarm pattern formation and transformation. Findings: A swarm pattern formation model based on mathematical foundations and macroscopic primitives is proposed. A formal definition for swarm pattern transformation and four special cases of transformation are introduced. Two general methods for transforming patterns are investigated and a comparison of the two methods is presented. The validity of the proposed models, and the feasibility of the methods investigated are confirmed on the Traer Physics and Processing environment. Originality/value: This paper helps in understanding the limitations of existing research in pattern formation and the lack of mathematical foundations for swarm systems. The mathematical model and transformation methods introduce two key concepts, namely macroscopic primitives and a mathematical model. The exercise of implementing the proposed models on physics simulator is novel.