A Fault-Tolerant Manipulator Robot Based on H(2), H(infinity), and Mixed H(2)/H(infinity) Markovian Controls

This paper develops a Markovian jump model to describe the fault occurrence in a manipulator robot of three joints. This model includes the changes of operation points and the probability that a fault occurs in an actuator. After a fault, the robot works as a manipulator with free joints. Based on the developed model, a comparative study among three Markovian controllers, H(2), H(infinity), and mixed H(2)/H(infinity) is presented, applied in an actual manipulator robot subject to one and two consecutive faults.

Coloured Petri nets and graphical simulation for the validation of a robotic cell in aircraft industry

This paper proposes a mixed validation approach based on coloured Petri nets and 3D graphic simulation for the design of supervisory systems in manufacturing cells with multiple robots. The coloured Petri net is used to model the cell behaviour at a high level of abstraction. It models the activities of each cell component and its coordination by a supervisory system. The graphical simulation is used to analyse and validate the cell behaviour in a 3D environment, allowing the detection of collisions and the calculation of process times. The motivation for this work comes from the aeronautic industry. The automation of a fuselage assembly process requires the integration of robots with other cell components such as metrological or vision systems. In this cell, the robot trajectories are defined by the supervisory system and results from the coordination of the cell components. The paper presents the application of the approach for an aircraft assembly cell under integration in Brazil. This case study shows the feasibility of the approach and supports the discussion of its main advantages and limits. (C) 2011 Elsevier Ltd. All rights reserved.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Topology optimization for designing strain-gauge load cells

Load cells are used extensively in engineering fields. This paper describes a novel structural optimization method for single- and multi-axis load cell structures. First, we briefly explain the topology optimization method that uses the solid isotropic material with penalization (SIMP) method. Next, we clarify the mechanical requirements and design specifications of the single- and multi-axis load cell structures, which are formulated as an objective function. In the case of multi-axis load cell structures, a methodology based on singular value decomposition is used. The sensitivities of the objective function with respect to the design variables are then formulated. On the basis of these formulations, an optimization algorithm is constructed using finite element methods and the method of moving asymptotes (MMA). Finally, we examine the characteristics of the optimization formulations and the resultant optimal configurations. We confirm the usefulness of our proposed methodology for the optimization of single- and multi-axis load cell structures.

Robotic Surgery: History and Teaching Impact

Context: The purpose of this article is to review the history of robotic surgery, its impact on teaching as well as a description of historical and current robots used in the medical arena. Summary of evidence: Although the history of robots dates back to 2000 years or more, the last two decades have seen an outstanding revolution in medicine, due to all the changes that robotic surgery has made in the way of performing, teaching and practicing surgery. Conclusions: Robotic surgery has evolved into a complete and self-contained field, with enormous potential for future development. The results to date have shown that this technology is capable of providing good outcomes and quality care for patients. (C) 2011 AEU. Published by Elsevier Espana, S.L. All rights reserved.

Conclusion

Teleneurology is the use of telecommunications to improve the delivery of neurology services. A wide range of telecommunications techniques may be used, including the telephone, email, the Internet and videoconferencing. Teleneurology can improve access to specialist neurological services for patients all over the world. Teleneurology also deals with more specialized fields that are of interest to the neurological practitioner, such as neurophysiology and neuroradiology. The book combines comprehensive reviews of each topic with practical advice on all available telemedicine techniques and on navigating the Internet for the most up-to-date neurological information. The fifth in a line of best selling telemedicine titles edited by Richard Wootton, Teleneurology is written by experts from four continents, providing a succinct introduction to teleneurology. It should prove invaluable for practising neurologists in particular, but also for general practitioners, paramedical staff, health service managers and IT staff. [via]

Effects of Prepartum Ingestion of Ipomoea carnea on Postpartum Maternal and Neonate Behavior in Goats

Ipomoea carnea is a toxic plant that grows in tropical areas, and is readily consumed by grazing goats. The plant contains the alkaloids swainsonine and calystegines, which inhibit cellular enzymes and cause systematic cell death. This study evaluated the behavioral effects on dams and kids of prenatal ingestion of this plant. Freshly harvested leaves of I. carnea (10 g/kg body weight) were fed daily to nine pregnant goats from the fifth to the 16th week of gestation; five pregnant goats were controls. Dam and kid behavior were evaluated during 2-hr postpartum. Further evaluation of the offspring was performed using various tests after birth: (1) reaching and discriminating their dam from an alien doe (two tests at 12-hr postpartum), and (2) navigating a progressive maze (2, 4, and 6 days postpartum). Postnatal (n=2) and fetal (n=2) mortality were observed in the treated group. Intoxicated kids had difficulty in standing at birth, and only one was able to suckle within 2 hr of birth. Treated kids were slower than controls to arrive at their dam in the discrimination test; treated kids often (seven of nine completed tests) incorrectly chose the alien dam (controls: 0/10 tests). During some runs on days 2, 4, and 6 postpartum, treated kids were slower to leave the starting point of the maze, and were slower to arrive at the dam on all test days. This study suggests that the offspring of pregnant goats given I. carnea during gestation have significant behavioral alterations and developmental delays. Birth Defects Res (Part B) 92:131-138, 2011. (C) 2011 Wiley-Liss, Inc.

Aprendizagem por imitação através de mapeamento Visuomotor baseado em imagens omnidirecionais

Este trabalho propõe uma metodologia de aprendizagem que permite a um robô aprender uma tarefa adaptando-a e representando-a de acordo com a sua capacidade motora e sensorial. Primeiramente, um mapeamento sensoriomotor é criado e converte informação sensorial em informação motora. Depois, através de imitação, o robô aprende um conjunto de ações elementares formando um vocabulário motor. A imitação é baseada nas representações motoras obtidas com o mapeamento sensoriomotor. O vocabulário motor criado é então utilizado para aprender e realizar tarefas mais sofisticadas, compostas por seqüências ou combinações de ações elementares. Esta metodologia é ilustrada através de uma aplicação de mapeamento e navegação topológica com um robô móvel. O automovimento é utilizado como mapeamento visuomotor, convertendo o fluxo óptico em imagens omnidirecionais em informação motora (translação e rotação), a qual é usada para a criação de um vocabulário motor. A seguir, o vocabulário é utilizado para mapeamento e navegação topológica. Os resultados obtidos são interessantes e a abordagem proposta pode ser estendida a diferentes robôs e aplicações.

Um algoritmo PSO híbrido para planejamento de caminhos em navegação de veículos utilizando A*

Utilizar robôs autônomos capazes de planejar o seu caminho é um desafio que atrai vários pesquisadores na área de navegação de robôs. Neste contexto, este trabalho tem como objetivo implementar um algoritmo PSO híbrido para o planejamento de caminhos em ambientes estáticos para veículos holonômicos e não holonômicos. O algoritmo proposto possui duas fases: a primeira utiliza o algoritmo A* para encontrar uma trajetória inicial viável que o algoritmo PSO otimiza na segunda fase. Por fim, uma fase de pós planejamento pode ser aplicada no caminho a fim de adaptá-lo às restrições cinemáticas do veículo não holonômico. O modelo Ackerman foi considerado para os experimentos. O ambiente de simulação de robótica CARMEN (Carnegie Mellon Robot Navigation Toolkit) foi utilizado para realização de todos os experimentos computacionais considerando cinco instâncias de mapas geradas artificialmente com obstáculos. O desempenho do algoritmo desenvolvido, A*PSO, foi comparado com os algoritmos A*, PSO convencional e A* Estado Híbrido. A análise dos resultados indicou que o algoritmo A*PSO híbrido desenvolvido superou em qualidade de solução o PSO convencional. Apesar de ter encontrado melhores soluções em 40% das instâncias quando comparado com o A*, o A*PSO apresentou trajetórias com menos pontos de guinada. Investigando os resultados obtidos para o modelo não holonômico, o A*PSO obteve caminhos maiores entretanto mais suaves e seguros.

Plataforma de controlo e simulação robótica

A robótica tem evoluído no sentido de criar robots e componentes cada vez mais evoluídos a preços acessíveis. Este facto permitiu que o desenvolvimento de aplicações no âmbito da robótica se tenha massificado e que a utilidade dos robots se tenha alargado a diferentes áreas de aplicação. Apesar da evolução dos robots e dos componentes para os mesmos, subsistem limitações que restringem a utilização de robots a certas aplicações, nomeadamente quando a capacidade de processamento e de memória não é suficiente para executar as aplicações. A forma para ultrapassar estas limitações tem residido essencialmente em duas abordagens: limitar as aplicações desenvolvidas à medida dos recursos disponíveis no hardware; ou estender as capacidades do robot usando recursos externos ao robot, quer por extensão do hardware do robot, quer por controlo remoto dos componentes do robot. Atendendo a esta problemática, foi desenvolvida uma plataforma que estende as capacidades dos robots segundo uma abordagem que usa o controlo remoto do robot, para capacitar as aplicações de controlo desenvolvidas de mais recursos, nomeadamente em termos de capacidade de processamento e memória. A plataforma desenvolvida disponibiliza ainda um simulador que virtualiza um campo de simulação e um robot, e simula a forma como estes interagem. O simulador é integrado na plataforma de forma semelhante aos adaptadores para robots, para que as aplicações desenvolvidas possam ser usadas quer em robots reais como no simulador.

An architecture for ambient intelligent environments

This paper presents the proposal of an architecture for developing systems that interact with Ambient Intelligence (AmI) environments. This architecture has been proposed as a consequence of a methodology for the inclusion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Systems Research for Ambient Intelligence). The ISyRAmI architecture considers several modules. The first is related with the acquisition of data, information and even knowledge. This data/information knowledge deals with our AmI environment and can be acquired in different ways (from raw sensors, from the web, from experts). The second module is related with the storage, conversion, and handling of the data/information knowledge. It is understood that incorrectness, incompleteness, and uncertainty are present in the data/information/knowledge. The third module is related with the intelligent operation on the data/information/knowledge of our AmI environment. Here we include knowledge discovery systems, expert systems, planning, multi-agent systems, simulation, optimization, etc. The last module is related with the actuation in the AmI environment, by means of automation, robots, intelligent agents and users.

Navegação de um robô autónomo semi-industrial usando diferentes técnicas sensoriais

Mestrado em Engenharia Electrotécnica e de Computadores

Optimização dos parâmetros de um robô hexápode através de algoritmos genéticos

Mestrado em Engenharia Electrotécnica e de Computadores

Construção de um robô trepador com locomoção através de rodas e adesão através de meios magnéticos

Mestrado em Engenharia Electrotécnica e de Computadores

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE