175 resultados para nonholonomic manipulator


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This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

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A crescente procura da bicicleta como meio de transporte alternativo torna relevante a criação e desenvolvimento de infra-estruturas de apoio, tais como ciclovias e parques para bicicletas. Os sistemas tradicionais de parqueamento de bicicletas com recurso a correntes e cadeados não fornecem segurança nem comodidade. No entanto, começam a surgir, em várias cidades do mundo, parque automáticos onde é possível guardar uma bicicleta em segurança, protegendo-a quer das intempéries quer de actos de vandalismo. Este trabalho apresenta uma proposta para um parque automático de armazenamento de bicicletas, com recurso a caixas individualizadas que garantem a sua segurança, e também de outros bens que podem ser guardados junto da mesma, como por exemplo um capacete ou uma mochila. O sistema proposto no âmbito deste trabalho é um complemento às alternativas existentes. As vantagens apresentadas pelo sistema proposto são: a sua construção modular e personalizada; e a possibilidade de instalação num terreno plano, sem recurso a obras de construção civil. O objectivo foi criar um projecto de automação e controlo de um protótipo, com base na proposta apresentada. O projecto de automação e controlo engloba a escolha dos sensores e dos actuadores. Para o dimensionamento dos motores foi necessário recorrer a um cálculo simplificado da estrutura do robô manipulador. Foi feita a escolha dos sensores, actuadores e do controlador com base nos requisitos funcionais. A programação foi desenvolvida numa linguagem normalizada. O modelo desenvolvido poderá servir de base para um projecto multidisciplinar entre vários departamentos do Instituto e dessa cooperação poderá surgir um novo projecto optimizado para produção e de menor custo.

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This paper studies fractional variable structure controllers. Two cases are considered namely, the sliding reference model and the control action, that are generalized from integer into fractional orders. The test bed consists in a mechanical manipulator and the effect of the fractional approach upon the system performance is evaluated. The results show that fractional dynamics, both in the switching surface and the control law are important design algorithms in variable structure controllers.

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Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those required to execute a given task. Several kinematic techniques for redundant manipulators control the gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and, moreover, often there are multiple optimization objectives that can conflict between them. Unlike single optimization, where one attempts to find the best solution, in multi-objective optimization there is no single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant robots remains an important area of research and more efficient optimization algorithms are needed. This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three or four rotational joints, considering the optimization of two objectives in a workspace without and with obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto optimal front according to the importance of each individual objective.

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This paper presents a fractional calculus perspective in the study of signals captured during the movement of a mechanical manipulator carrying a liquid container. In order to study the signals an experimental setup is implemented. The system acquires data from the sensors, in real time, and, in a second phase, processes them through an analysis package. The analysis package runs off-line and handles the recorded data. The results show that the Fourier spectrum of several signals presents a fractional behavior. The experimental study provides useful information that can assist in the design of a control system and the trajectory planning to be used in reducing or eliminating the effect of vibrations.

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The trajectory planning of redundant robots through the pseudoinverse control leads to undesirable drift in the joint space. This paper presents a new technique to solve the inverse kinematics problem of redundant manipulators, which uses a fractional differential of order α to control the joint positions. Two performance measures are defined to examine the strength and weakness of the proposed method. The positional error index measures the precision of the manipulator's end-effector at the target position. The repeatability performance index is adopted to evaluate if the joint positions are repetitive when the manipulator execute repetitive trajectories in the operational workspace. Redundant and hyper-redundant planar manipulators reveal that it is possible to choose in a large range of possible values of α in order to get repetitive trajectories in the joint space.

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In practice the robotic manipulators present some degree of unwanted vibrations. The advent of lightweight arm manipulators, mainly in the aerospace industry, where weight is an important issue, leads to the problem of intense vibrations. On the other hand, robots interacting with the environment often generate impacts that propagate through the mechanical structure and produce also vibrations. In order to analyze these phenomena a robot signal acquisition system was developed. The manipulator motion produces vibrations, either from the structural modes or from endeffector impacts. The instrumentation system acquires signals from several sensors that capture the joint positions, mass accelerations, forces and moments, and electrical currents in the motors. Afterwards, an analysis package, running off-line, reads the data recorded by the acquisition system and extracts the signal characteristics. Due to the multiplicity of sensors, the data obtained can be redundant because the same type of information may be seen by two or more sensors. Because of the price of the sensors, this aspect can be considered in order to reduce the cost of the system. On the other hand, the placement of the sensors is an important issue in order to obtain the suitable signals of the vibration phenomenon. Moreover, the study of these issues can help in the design optimization of the acquisition system. In this line of thought a sensor classification scheme is presented. Several authors have addressed the subject of the sensor classification scheme. White (White, 1987) presents a flexible and comprehensive categorizing scheme that is useful for describing and comparing sensors. The author organizes the sensors according to several aspects: measurands, technological aspects, detection means, conversion phenomena, sensor materials and fields of application. Michahelles and Schiele (Michahelles & Schiele, 2003) systematize the use of sensor technology. They identified several dimensions of sensing that represent the sensing goals for physical interaction. A conceptual framework is introduced that allows categorizing existing sensors and evaluates their utility in various applications. This framework not only guides application designers for choosing meaningful sensor subsets, but also can inspire new systems and leads to the evaluation of existing applications. Today’s technology offers a wide variety of sensors. In order to use all the data from the diversity of sensors a framework of integration is needed. Sensor fusion, fuzzy logic, and neural networks are often mentioned when dealing with problem of combing information from several sensors to get a more general picture of a given situation. The study of data fusion has been receiving considerable attention (Esteban et al., 2005; Luo & Kay, 1990). A survey of the state of the art in sensor fusion for robotics can be found in (Hackett & Shah, 1990). Henderson and Shilcrat (Henderson & Shilcrat, 1984) introduced the concept of logic sensor that defines an abstract specification of the sensors to integrate in a multisensor system. The recent developments of micro electro mechanical sensors (MEMS) with unwired communication capabilities allow a sensor network with interesting capacity. This technology was applied in several applications (Arampatzis & Manesis, 2005), including robotics. Cheekiralla and Engels (Cheekiralla & Engels, 2005) propose a classification of the unwired sensor networks according to its functionalities and properties. This paper presents a development of a sensor classification scheme based on the frequency spectrum of the signals and on a statistical metrics. Bearing these ideas in mind, this paper is organized as follows. Section 2 describes briefly the robotic system enhanced with the instrumentation setup. Section 3 presents the experimental results. Finally, section 4 draws the main conclusions and points out future work.

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This chapter analyzes the signals captured during impacts and vibrations of a mechanical manipulator. Eighteen signals are captured and several metrics are calculated between them, such as the correlation, the mutual information and the entropy. A sensor classification scheme based on the multidimensional scaling technique is presented.

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Most machining tasks require high accuracy and are carried out by dedicated machine-tools. On the other hand, traditional robots are flexible and easy to program, but they are rather inaccurate for certain tasks. Parallel kinematic robots could combine the accuracy and flexibility that are usually needed in machining operations. Achieving this goal requires proper design of the parallel robot. In this chapter, a multi-objective particle swarm optimization algorithm is used to optimize the structure of a parallel robot according to specific criteria. Afterwards, for a chosen optimal structure, the best location of the workpiece with respect to the robot, in a machining robotic cell, is analyzed based on the power consumed by the manipulator during the machining process.

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This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. To test the impacts, a flexible beam is clamped to the end-effector of a manipulator that is programmed in a way such that the rod moves against a rigid surface. Eighteen signals are captured and theirs correlation are calculated. A sensor classification scheme based on the multidimensional scaling technique is presented.

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The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. The pseudoinverse control is not repeatable, causing drift in joint space which is undesirable for physical control. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms, leading to an optimization criterion for repeatable control of redundant manipulators, and avoiding the joint angle drift problem. Computer simulations performed based on redundant and hyper-redundant planar manipulators show that, when the end-effector traces a closed path in the workspace, the robot returns to its initial configuration. The solution is repeatable for a workspace with and without obstacles in the sense that, after executing several cycles, the initial and final states of the manipulator are very close.

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This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. In order to acquire and study the signals an experimental setup is implemented. The signals are treated through signal processing tools such as the fast Fourier transform and the short time Fourier transform. The results show that the Fourier spectrum of several signals presents a non integer behavior. The experimental study provides valuable results that can assist in the design of a control system to deal with the unwanted effects of vibrations.

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This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. The Fourier Transform of eighteen different signals are calculated and approximated by trendlines based on a power law formula. A sensor classification scheme based on the frequency spectrum behavior is presented.

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This work proposes a real-time algorithm to generate a trajectory for a 2 link planar robotic manipulator. The objective is to minimize the space/time ripple and the energy requirements or the time duration in the robot trajectories. The proposed method uses an off line genetic algorithm to calculate every possible trajectory between all cells of the workspace grid. The resultant trajectories are saved in several trees. Then any trajectory requested is constructed in real-time, from these trees. The article presents the results for several experiments.

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RESUMO: O uso de ratinhos transgénicos em neurociências aumentou consideravelmente nos últimos anos devido ao crescente interesse em compreender o cérebro e a necessidade de solucionar situações clínicas do foro neurológico e psiquiátrico. Para esse efeito, diferentes métodos de produção de animais transgénicos têm sido testados. O objectivo desta tese foi comparar métodos de integração aleatória de um transgene no genoma de ratinhos em termos de eficiência, estabilidade da integração do transgene, número de animais e de horas de trabalho necessárias para cada método. Assim, foi comparado o método mais utilizado - microinjecção pronuclear (PNMI) - com duas outras técnicas cujo desempenho foi considerado promissor – a transferência génica através dos testículos por electroporação e transfecção por lentivírus in vivo. As três técnicas foram realizadas usando um gene repórter sob o controlo de um promotor constitutivo, e depois reproduzidas usando um gene de interesse de modo a permitir obtenção de um animal capaz de ser usado em experimentação laboratorial. O transgene de interesse utilizado codifica uma proteína de fusão correspondendo a uma variante da rodopsina (channelrhodopsin) fundida à proteína enhanced yellow fluorescente protein ((EYFP) resultando num produto designado ChR2-EYFP. Este animal transgénico apresentaria expressão deste canal iónico apenas em células dopaminergicas, o que, com manipulação optogenética, tornaria possivel a activação especifica deste grupo de neurónios e, simultaneamente, a observação do impacto desta manipulação no comportamento num animal em livre movimento. Estas ferramentas são importantes na investigação básica em neurociências pois ajudam a esclarecer o papel de grupos específicos de neurónios e compreender doenças como a doença de Parkinson ou a esquizofrenia onde a função de certos tipos de neurónios de encontra alterada. Quando comparados os três métodos realizados verifica-se que usando um gene repórter PMNI resulta em 31,3% de, a de animais transgénicos obtidos, a electroporação de testículos em 0% e a injecção de lentivírus em 0%. Quando usado o gene de interesse, os resultados obtidos são, respectivamente, 18,8%, 63,9% e 0%.--------------ABSTRACT: The use of transgenic mice is increasing in all fields of research, particularly in neuroscience, due to the widespread need of animal models to solve neurological and psychiatric medical conditions. Different methodologies have been tested in the last decades in order to produce such transgenic animals. The ultimate goal of this thesis is to compare different methods of random integration of a transgene in the genome of mice in terms of efficiency, stability of the transgene integration, number of animals required and the labour intensity of each technique. We compared the most used method – pronuclear microinjection (PNMI) – with two other promising techniques – Testis Mediated Gene Transfer (TMGT) by electroporation and in vivo lentiviral transfection. The three techniques were performed using a reporter gene – green fluorescent protein (GFP), whose transcription was driven by the constitutive cytomegalovirus (CMV) promoter. These three techniques were later reproduced using the tyrosine hydroxylase promoter (TH) and the neuronal manipulator, channelrhodopsin-2 fused to the enhanced yellow fluorescent reporter protein (ChR2-EYFP). The transgenic animal we sough to produce would express the light driven channel only in dopaminergic cells, making possible to specifically activate this group of neurons, while simultaneously observe the behaviour in a freely moving animal. This is a very important tool in basic neuroscience research since it helps to clarify the role of specific groups of neurons, map circuits in the brain, and consequently understand neurological diseases such as Parkinson’s disease or schizophrenia, where the function of certain types of neurons is affected. When comparing the three methods, it was verified that using a reporter gene PNMI resulted in 31.3% of transgenic mice obtained, testis electroporation in 0% and lentiviral injection in 0%. When using the gene of interest, the results obtained were, respectively, 18.8%, 63.9% and 0%.