877 resultados para Simulated robots
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A robot’s drive has to exert appropriate driving forces that can keep its arm and end effector at the proper position, velocity and acceleration, and simultaneously has to compensate for the effects of the contact forces arising between the tool and the workpiece depending on the needs of the actual technological operation. Balancing the effects of a priori unknown external disturbance forces and the inaccuracies of the available dynamic model of the robot is also important. Technological tasks requiring well prescribed end effector trajectories and contact forces simultaneously are challenging control problems that can be tackled in various manners.
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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 this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.
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The interest in the development of climbing robots is growing rapidly. Motivations are typically to increase the operation efficiency by obviating the costly assembly of scaffolding or to protect human health and safety in hazardous tasks. Climbing robots are starting to be developed for applications ranging from cleaning to inspection of difficult to reach constructions. These robots should be capable of travelling on different types of surfaces, with varying inclinations, such as floors, walls, ceilings, and to walk between such surfaces. Furthermore, these machines should be capable of adapting and reconfiguring for various environment conditions and to be self-contained. Regarding the adhesion to the surface, they should be able to produce a secure gripping force using a light-weight mechanism. This paper presents a survey of different applications and technologies proposed for the implementation of climbing robots.
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This article studies several Fractional Order Control algorithms used for joint control of a hexapod robot. Both Padé and series approximations to the fractional derivative are considered for the control algorithm. The walking performance is evaluated through two indices: The mean absolute density of energy used per unit distance travelled, and the control effort. A set of simulation experiments reveals the influence of the different approximations upon the proposed indices. The results show that the fractional proportional and derivative algorithm, implemented using the Padé approximation with a small number of terms, gives the best results.
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The objective of this paper is to present the evolution and the state-of-the-art in the area of legged locomotion systems. In a first phase different possibilities for implementing mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations. In a second phase a historical overview of the evolution of these systems is presented, bearing in mind several particular cases often considered as milestones of technological and scientific progress. After this historical timeline, some of the present-day systems are examined and their performance is analyzed. In a third phase the major areas of research and development that are presently being followed in the construction of legged robots are pointed out. Finally, some still unsolved problems that remain defying robotics research, are also addressed.
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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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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.
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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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The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.
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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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The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.
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The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.
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An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.
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Este trabalho foi elaborado no âmbito do Mestrado de Ensino de Matemática do 3º Ciclo do Ensino Básico e Secundário da Universidade da Madeira, no ano letivo de 2012/2013. Os grandes objetivos deste estudo são os de analisar qualitativamente uma atividade, para compreender como é que os alunos aprendem trigonometria, utilizando os robots NXT da Lego. De igual modo, se procede também, de forma sucinta, à apresentação do trabalho desenvolvido pelo grupo de estágio, ao longo da Prática de Ensino Supervisionado. Para a realização da investigação, foram recolhidos dados pelo investigador, através de registos audiovisuais do trabalho dos alunos, com câmara e vídeo. Com o fim de melhor estudar o problema aqui apresentado, o mesmo foi dissecado em três questões de investigação: (a) Que aprendizagens os alunos realizam com a montagem, programação e interação com os robots? (b) De que forma é que os alunos aprendem trigonometria, quando utilizam os Robots? (c) Quais as dificuldades manifestadas pelos alunos na resolução de problemas? As questões de investigação iluminaram a análise dos dados. Das conclusões que advêm deste estudo destaca-se o papel essencial da robótica e dos materiais manipuláveis, na construção e concetualização do conhecimento dos alunos.