71 resultados para Planning of movement

em Instituto Politécnico do Porto, Portugal


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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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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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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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The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms. The results are compared with a genetic algorithm that adopts the direct kinematics. In both cases the trajectory planning is formulated as an optimization problem with constraints.

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Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

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Introduction Myocardial Perfusion Imaging (MPI) is a very important tool in the assessment of Coronary Artery Disease ( CAD ) patient s and worldwide data demonstrate an increasingly wider use and clinical acceptance. Nevertheless, it is a complex process and it is quite vulnerable concerning the amount and type of possible artefacts, some of them affecting seriously the overall quality and the clinical utility of the obtained data. One of the most in convenient artefacts , but relatively frequent ( 20% of the cases ) , is relate d with patient motion during image acquisition . Mostly, in those situations, specific data is evaluated and a decisi on is made between A) accept the results as they are , consider ing that t he “noise” so introduced does not affect too seriously the final clinical information, or B) to repeat the acquisition process . Another possib ility could be to use the “ Motion Correcti on Software” provided within the software package included in any actual gamma camera. The aim of this study is to compare the quality of the final images , obtained after the application of motion correction software and after the repetition of image acqui sition. Material and Methods Thirty cases of MPI affected by Motion Artefacts and repeated , were used. A group of three, independent (blinded for the differences of origin) expert Nuclear Medicine Clinicians had been invited to evaluate the 30 sets of thre e images - one set for each patient - being ( A) original image , motion uncorrected , (B) original image, motion corrected, and (C) second acquisition image, without motion . The results so obtained were statistically analysed . Results and Conclusion Results obtained demonstrate that the use of the Motion Correction Software is useful essentiall y if the amplitude of movement is not too important (with this specific quantification found hard to define precisely , due to discrepancies between clinicians and other factors , namely between one to another brand); when that is not the case and the amplitude of movement is too important , the n the percentage of agreement between clinicians is much higher and the repetition of the examination is unanimously considered ind ispensable.

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Objective: The purpose of this study was to investigate effects of different manual techniques on cervical ranges of 17 motion and pressure pain sensitivity in subjects with latent trigger point of the upper trapezius muscle. 18 Methods: One hundred seventeen volunteers, with a unilateral latent trigger point on upper trapezius due to computer 19 work, were randomly divided into 5 groups: ischemic compression (IC) group (n = 24); passive stretching group (n = 20 23); muscle energy technique group (n = 23); and 2 control groups, wait-and-see group (n = 25) and placebo group 21 (n = 22). Cervical spine range of movement was measured using a cervical range of motion instrument as well as 22 pressure pain sensitivity by means of an algometer and a visual analog scale. Outcomes were assessed pretreatment, 23 immediately, and 24 hours after the intervention and 1 week later by a blind researcher. A 4 × 5 mixed repeated- 24 measures analysis of variance was used to examine the effects of the intervention and Cohen d coefficient was used. 25 Results: A group-by-time interaction was detected in all variables (P b .01), except contralateral rotation. The 26 immediate effect sizes of the contralateral flexion, ipsilateral rotation, and pressure pain threshold were large for 3 27 experimental groups. Nevertheless, after 24 hours and 1 week, only IC group maintained the effect size. 28 Conclusions: Manual techniques on upper trapezius with latent trigger point seemed to improve the cervical range of 29 motion and the pressure pain sensitivity. These effects persist after 1 week in the IC group. (J Manipulative Physiol 301 Ther 2013;xx:1-10)

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In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.

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The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

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The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

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The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

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Projecto apresentado ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Assessoria de Administração

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Objectivo: Pretendeu-se avaliar as modificações no comportamento neuro-motor a nível da funcionalidade do membro superior predominantemente afectado e a sua influência no ciclo da marcha de dois indivíduos com Acidente Vascular Cerebral, face a um programa de intervenção em fisioterapia, segundo uma abordagem baseada no Conceito de Bobath. Foi também objectivo averiguar o impacto qualitativo nos componentes e estados de saúde. Metodologia: A avaliação foi realizada em dois indivíduos com sequelas de Acidente Vascular Cerebral, antes e após o plano de intervenção segundo o Conceito de Bobath, através do registo observacional, da Classificação Internacional de Funcionalidade, Incapacidade e Saúde, da Performance-Oriented Mobility Assessment POMA I, da Time Up and Go Test, da Motor Assessement Scale e da Motor Evaluation Scale for Upper Extremity in Patients. Resultados: Obteve-se um incremento da funcionalidade do membro superior predominantemente afectado, com uma atribuição na Classificação Internacional de Funcionalidade, Incapacidade e Saúde de qualificadores correspondentes a dificuldade ligeira a moderada ao nível da mobilidade e dos auto cuidado após o plano de intervenção, repercutindo-se assim numa diminuição da restrição na participação e limitação da actividade. Houve um aumento de score total em todos os instrumentos e escalas de medidas de avaliação utilizadas, tendo os indivíduos alcançado uma maior funcionalidade do membro superior e um padrão de marcha mais eficiente, com uma menor necessidade de recorrer a estratégias compensatórias de movimento. Conclusão: O plano de intervenção, baseado numa abordagem segundo o Conceito de Bobath, essencialmente dirigido para a obtenção de ganhos funcionais ao nível do membro superior predominantemente afectado nos indivíduos em estudo, parece ter contribuído para induzir mudanças no comportamento neuro-motor, verificando-se uma influência no ciclo de marcha ao nível da qualidade e eficiência do movimento.

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Objectivo Pretende-se verificar a influência de um programa de intervenção em fisioterapia, dirigido para o aumento do nível de actividade do tronco, bem como a sua relação em termos funcionais com o movimento de alcançar, em indivíduos pós Acidente Vascular Encefálico. Metodologia Amostra constituída por 2 elementos pós AVE. Após avaliação inicial identificou-se como principal problema a diminuição do nível de actividade do tronco. Foi implementado um programa de intervenção baseado num processo e raciocínio clínico durante 2 meses, tendo sido aplicado antes e depois, os instrumentos Functional Reach, Escala de Ashworth e Classificação Internacional de Funcionalidade, Incapacidade e Saúde. Resultados Melhoria na avaliação dos componentes de movimento durante os gestos funcionais, assim como se verificou um aumento da estabilidade anterior e uma diminuição do tónus muscular. Após a intervenção observa-se o envolvimento do membro superior em actividades funcionais. Conclusão Um programa de intervenção direccionado para o aumento do nível de actividade do tronco pode-se obter um movimento de alcance mais funcional durante as AVD´s e uma diminuição do tónus muscular do MS.

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AGM and Conference in Mechelen 27 – 30 April 2010