Over the last decades, the worldwide increase in cases of neuromotor health issues, due to overall population aging, motivated a growing research interest in improving rehabilitation processes with robotics. The performed studies opened the possibility to include other auxiliary technologies in physical and occupational therapy, like virtual reality and remote interaction between patients and therapists. Although there are verified and potential benefits to rehabilitation provided by these techniques, there are still few attempts towards tooling and methodology standardization, which could lead to faster developments. This work describes the creation of a proposed common computational platform for robotic rehabilitation studies, with support for virtual games and telecommunication. A preceding literature review helped to determine the requirements and development tools for such multipurpose system. Its modular and configurable design aims to allow components reuse and adaptability to different robotic therapy cases, even ones not initially intended, preventing work duplication. Details about the system\'s structure, components and operation are shown, focusing its provided flexibility. Multiplayer games involving position and force control are also created to test the proposed system in real and simulated environment, in order to demonstrate its usability for application and evaluation of robotic rehabilitation strategies. At the end, the results obtained so far are discussed and considerations about missing points and future developments are made. / Nas últimas décadas, o aumento global nos casos de problemas de saúde neuromotores, devido ao envelhecimento da população, motivou um interesse crescente na pesquisa sobre melhoria de processos de rehabilitação utilizando robótica. Os estudos realizados realizados abriram possibilidade de se incluir outras tecnologias auxiliares na terapia física e ocupacional, como realidade virtual e interação remota entre pacientes e terapeutas. Apesar dos benefícios verificados ou potenciais da aplicação dessas técnicas, ainda há poucas iniciativas no sentido de padronizar ferramentas e metodologias para sua implementação e teste, o que poderia catalisar os avanços na área. Esse trabalho descreve a criação de uma plataforma computacional comum para estudos de Reabilitação Robótica, com suporte a utilização de Jogos Sérios e teleoperação. Uma revisão bibliográfica prévia ajudou a definir os requisitos e ferramentas de desenvolvimento adequadas para tal sistema multipropósito. Seu projeto modular e configurável tem o intuito de permitir reutilização de componentes e sua fácil adaptação a diferentes tipos de terapia, mesmo não inicialmente planejadas, evitando duplicação de trabalho. Jogos multijogador envolvendo controle de força e posição são também criados para testar o sistema proposto em situações reais ou simuladas, de modo a demonstrar sua utilidade para aplicação Detalhes de sua estrutura de operação, protocolos de comunicação e componentes são mostrados, destacando-se a flexibilidade oferecida. Testes simples de viabilidade com indivíduos saudáveis são realizados, a fim de demonstrar sua utilidade para aplicação e avaliação de estratégias de reabilitação robótica. Ao fim, os resultados obtidos até então são discutidos, e considerações sobre informações ainda faltantes e trabalhos futuros são feitas.

Este trabalho apresenta uma comparação entre as estratégias de controle por torque calculado e controle repetitivo aplicadas a manipuladores robóticos. O objetivo no uso desses controladores é para que o manipulador siga referência de trajetória periódica no espaço das juntas. O desenvolvimento e implementação dos controladores são focados no manipulador WAM (Whole Arm Manipulator) da Barrett Technology®Inc. Neste trabalho, também são apresentadas uma formulação do modelo não linear do manipulador e as sínteses dos controladores por torque calculado e repetitivo aplicados ao modelo do manipulador linearizado por realimentação. O controlador por torque calculado é apresentado e sintetizado na sua forma clássica. Para o controlador repetitivo, a síntese parte do princípio do modelo interno com a adição de uma estrutura repetitiva e uma realimentação proporcional e derivativa do erro de seguimento de referência O projeto dos ganhos do controlador repetitivo é feito através de um problema de otimização convexa com restrições na forma de inequações matriciais lineares (ou no inglês: Linear Matrix Inequalities - LMI). A formulação do problema de otimização parte da teoria de estabilidade segundo Lyapunov com um funcional Lyapunov-Krasoviskii, adição de um custo quadrático, para ajuste de desempenho, e de um critério de desempenho transitório dado pela taxa de decaimento exponencial da norma dos estados. É apresentada a comparação entre as estratégias de controle e a validação do controlador repetitivo proposto aplicado ao caso com linearização perfeita e ao caso com o modelo não linear do manipulador. No primeiro caso, é feita a simulação do modelo linear do manipulador com adição de um torque de atrito na junta. No segundo caso, é utilizado o sistema ROS (Robot Operating System) com o programa Gazebo simulando o manipulador WAM considerando erros de linearização, isto é, incertezas paramétricas. / This work presents a comparison between the strategies of computed-torque control and repetitive control applied to robotic manipulators. The main objective in use these controllers with the manipulator is to tracking periodic trajectory in joint space. The development and implementation of controllers are focused on the Whole Arm Manipulator (WAM) of the Barrett Technology®Inc. Also featured are a non-linear model formulation of the manipulator and the synthesis of controllers for computed-torque control and repetitive control applied to the manipulator model linearized by state feedback. The computed-torque controller is presented in its classic form. For the repetitive controller, the synthesis is based on the internal model principle with the addition of a repetitive structure and a proportional-derivative reference tracking error feedback. The design of the repetitive controller gains is done through a convex optimization problem with linear matrix inequalities (LMI) constraints. The formulation of the optimization problem is based on the Lyapunov stability theory using a Lyapunov-Krasoviskii functional, addition of a quadratic cost for performance adjustment and a transient performance criteria given by the exponential decay rate of the states norm. A comparison between the control strategies and the validation of the repetitive controller applied to the case with perfect linearization and the case with the non-linear model of the manipulator are presented. In the first case, is made simulations of the linear model of the manipulator in MATLAB program, with the addition of a disturbance modeling the friction torque at the joint. In the second case, is used the Robot Operating System (ROS) with Gazebo program simulating the WAM nonlinear model. In this case, a possible mismatch between the model used for the feedback linearization and the real system is taken into account.

Tungsten Inert Gas (TIG) welding is extensively used in aerospace applications, due to its unique ability to produce higher quality welds compared to other shielded arc welding types. However, most TIG welding is performed manually and has not achieved the levels of automation that other welding techniques have. This is mostly attributed to the lack of process knowledge and adaptability to complexities, such as mismatches due to part fit-up. Recent advances in automation have enabled the use of industrial robots for complex tasks that require intelligent decision making, predominantly through sensors. Applications such as TIG welding of aerospace components require tight tolerances and need intelligent decision making capability to accommodate any unexpected variation and to carry out welding of complex geometries. Such decision making procedures must be based on the feedback about the weld profile geometry. In this thesis, a real-time position based closed loop system was developed with a six axis industrial robot (KUKA KR 16) and a laser triangulation based sensor (Micro-Epsilon Scan control 2900-25).

Even with the advance of autonomous robotics and automation, many automated tasks still require human intervention or guidance to mediate uncertainties in the environment or to execute the complexities of a task that autonomous robots are not yet equipped to handle. As such, robot controllers are needed that utilize the strengths of both autonomous agents, adept at handling lower level control tasks, and humans, superior at handling higher-level cognitive tasks. To address this need, we develop a control theoretic framework that seeks to incorporate user commands such that user intention is preserved while an automated task is carried out by the controller. This is a novel approach in that system theoretic tools allow for analytic guarantees of feasibility and convergence to goal states which naturally lead to varying levels of autonomy. We develop a model predictive controller that takes human input, infers human intent, then applies a control that minimizes deviations from the intended human control while ensuring that the lower-level automated task is being completed. This control framework is then evaluated in a human operator study involving a shared control task with human guidance of a mobile robot for navigation. These theoretical and experimental results lay the foundation for applying this control method for human-robot cooperative control to actual human-robot tasks. Specifically, the control is applied to a Urban Search and Rescue robot task where the shared control of a quadruped rescue robot is needed to ensure static stability during human-guided leg placements in uneven terrain. This control framework is also extended to a multiple user and multiple agent system where the human operators control multiple agents such that the agents maintain a formation while allowing the human operators to manipulate the shape of the formation. User studies are also conducted to evaluate the control in multiple operator scenarios.

<p>This thesis consists of four independent papers concerningthe control of mobile robots in the context of obstacleavoidance and formation keeping.</p><p>The first paper describes a new theoreticallyv erifiableapproach to obstacle avoidance. It merges the ideas of twoprevious methods, with complementaryprop erties, byusing acombined control Lyapunov function (CLF) and model predictivecontrol (MPC) framework.</p><p>The second paper investigates the problem of moving a fixedformation of vehicles through a partiallykno wn environmentwith obstacles. Using an input to state (ISS) formulation theconcept of configuration space obstacles is generalized toleader follower formations. This generalization then makes itpossible to convert the problem into a standard single vehicleobstacle avoidance problem, such as the one considered in thefirst paper. The properties of goal convergence and safetyth uscarries over to the formation obstacle avoidance case.</p><p>In the third paper, coordination along trajectories of anonhomogenuos set of vehicles is considered. Byusing a controlLyapunov function approach, properties such as boundedformation error and finite completion time is shown.</p><p>Finally, the fourth paper applies a generalized version ofthe control in the third paper to translate,rotate and expanda formation. It is furthermore shown how a partial decouplingof formation keeping and formation mission can be achieved. Theapproach is then applied to a scenario of underwater vehiclesclimbing gradients in search for specific thermal/biologicalregions of interest. The sensor data fusion problem fordifferent formation configurations is investigated and anoptimal formation geometryis proposed.</p><p><b>Keywords:</b>Mobile Robots, Robot Control, ObstacleAvoidance, Multirobot System, Formation Control, NavigationFunction, Lyapunov Function, Model Predictive Control, RecedingHorizon Control, Gradient Climbing, Gradient Estimation.</p>

Neuroninė kompiuterio sąsaja – tai alternatyvus būdas valdyti kompiuterį nenaudojant rankų. Ji gali būti apibrėžta, kaip komunikavimo sistema, kuri leidžia valdyti kompiuterį ar kitą skaitmeninį įrenginį, naudojant nervinės kilmės fiziologinius signalus. Pagrindinė neuroninės kompiuterio sąsajos taikymo sritis yra neįgaliesiems skirti įrenginiai. Tai ne tik specifiniai įrenginiai, tokie, kaip galūnių protezai, tačiau ir kompiuteriai su papildoma aparatine ir programine įranga, kuri leidžia žmonėms, nevaldantiems rankų, valdyti kompiuterį. Taip pat išmanieji invalido vežimėliai, kuriuos galima vairuoti nenaudojant rankų judesių. Šiame darbe analizuojama neuroninė kompiuterio sąsaja, skirta vežimėlio tipo roboto valdymui. Pateikiama mūsų sukurta neuroninės kompiuterio sąsajos sistema, gebanti nuskaityti žmogaus EEG ir galvos raumenų EMG signalus, juos apdoroti, klasifikuoti ir jų pagalba valdyti vežimėlio tipo robotą. Taip pat pateikiamas trijų komandų vežimėlio tipo roboto valdymo per galvos paviršinio EMG signalo lygį metodas. Pateikiami roboto valdymo taikant šį metodą tikslumo eksperimentai ir jų rezultatai. / Neural computer interface is alternative way to control computer without hands. It is defined as a communication system which allows user control computer or any other digital device using neural breed physiological signal. The main application of neural computer interface is various devices for people with disabilities. For example, electronic prosthetic limbs, PC‘s with additional hardware and software which allows people with motor disabilities to control PC or intelligent wheelchairs. In this work we are analyzing neural computer interface applied for robot control. The author presents neural computer interface system which allows to read EEG and head surface EMG signals, pre-process the signals, classify the signals and control Arduino 4WD robot. We also propose approach to control robot with head surface EMG signal amplitude using 3 control commands. Robot control research using proposed approach is presented.

In advanced robot applications, the challenge today is that the robot should perform different successive subtasks to achieve one or more complicated tasks similar to human. Hence, this kind of tasks required to combine different kind of sensors in order to get full information about the work environment. However, from the point of view of control, more sensors mean more possibilities for the structure of the control system. As shown previously, vision and force sensors are the most common external sensors in robot system. As a result, in scientific papers it can be found numerous control algorithms and different structures for vision/force robot control, e.g. shared, traded control etc. The lacks in integration of vision/force robot control could be summarized as follows: • How to define which subspaces should be vision, position or force controlled? • When the controller should switch from one control mode to another one? • How to insure that the visual information could be reliably used? • How to define the most appropriated vision/force control structure? In many previous works, during performing a specified task one kind of vision/force control structure has been used which is pre-defined by the programmer. In addition to that, if the task is modified or changed, it would be much complicated for the user to describe the task and to define the most appropriated vision/force robot control especially if the user is inexperienced. Furthermore, vision and force sensors are used only as simple feedback (e.g. vision sensor is used usually as position estimator) or they are intended to avoid the obstacles. Accordingly, much useful information provided by the sensors which help the robot to perform the task autonomously is missed. In our opinion, these lacks of defining the most appropriate vision/force robot control and the weakness in the utilization from all the information which could be provided by the sensors introduce important limits which prevent the robot to be versatile, autonomous, dependable and user-friendly. For this purpose, helping to increase autonomy, versatility, dependability and user-friendly in certain area of robotics which requires vision/force integration is the scope of this thesis. More concretely: 1. Autonomy: In the term of an automatic decision system which defines the most appropriated vision/force control modes for different kinds of tasks and chooses the best structure of vision/force control depending on the surrounding environments and a priori knowledge. 2. Versatility: By preparing some relevant scenarios for different situations, where both the visual servoing and force control are necessary and indispensable. 3. Dependability: In the term of the robot should depend on its own sensors more than on reprogramming and human intervention. In other words, how the robot system can use all the available information which could be provided by the vision and force sensors, not only for the target object but also for the features extraction of the whole scene. 4. User-friendly: By designing a high level description of the task, the object and the sensor configuration which is suitable also for inexperienced user. If the previous properties are relatively achieved, the proposed robot system can: • Perform different successive and complex tasks. • Grasp/contact and track imprecisely placed objects with different poses. • Decide automatically the most appropriate combination of vision/force feedback for every task and react immediately to the changes from one control cycle to another because of occurrence of some unforeseen events. • Benefit from all the advantages of different vision/force control structures. • Benefit from all the information provided by the sensors. • Reduce the human intervention or reprogramming during the execution of the task. • Facilitate the task description and entering of a priori-knowledge for the user, even if he/she is inexperienced.

This thesis consists of four independent papers concerningthe control of mobile robots in the context of obstacleavoidance and formation keeping. The first paper describes a new theoreticallyv erifiableapproach to obstacle avoidance. It merges the ideas of twoprevious methods, with complementaryprop erties, byusing acombined control Lyapunov function (CLF) and model predictivecontrol (MPC) framework. The second paper investigates the problem of moving a fixedformation of vehicles through a partiallykno wn environmentwith obstacles. Using an input to state (ISS) formulation theconcept of configuration space obstacles is generalized toleader follower formations. This generalization then makes itpossible to convert the problem into a standard single vehicleobstacle avoidance problem, such as the one considered in thefirst paper. The properties of goal convergence and safetyth uscarries over to the formation obstacle avoidance case. In the third paper, coordination along trajectories of anonhomogenuos set of vehicles is considered. Byusing a controlLyapunov function approach, properties such as boundedformation error and finite completion time is shown. Finally, the fourth paper applies a generalized version ofthe control in the third paper to translate,rotate and expanda formation. It is furthermore shown how a partial decouplingof formation keeping and formation mission can be achieved. Theapproach is then applied to a scenario of underwater vehiclesclimbing gradients in search for specific thermal/biologicalregions of interest. The sensor data fusion problem fordifferent formation configurations is investigated and anoptimal formation geometryis proposed. Keywords:Mobile Robots, Robot Control, ObstacleAvoidance, Multirobot System, Formation Control, NavigationFunction, Lyapunov Function, Model Predictive Control, RecedingHorizon Control, Gradient Climbing, Gradient Estimation. / QC 20111121

Este trabalho apresenta uma comparação entre as estratégias de controle por torque calculado e controle repetitivo aplicadas a manipuladores robóticos. O objetivo no uso desses controladores é para que o manipulador siga referência de trajetória periódica no espaço das juntas. O desenvolvimento e implementação dos controladores são focados no manipulador WAM (Whole Arm Manipulator) da Barrett Technology®Inc. Neste trabalho, também são apresentadas uma formulação do modelo não linear do manipulador e as sínteses dos controladores por torque calculado e repetitivo aplicados ao modelo do manipulador linearizado por realimentação. O controlador por torque calculado é apresentado e sintetizado na sua forma clássica. Para o controlador repetitivo, a síntese parte do princípio do modelo interno com a adição de uma estrutura repetitiva e uma realimentação proporcional e derivativa do erro de seguimento de referência O projeto dos ganhos do controlador repetitivo é feito através de um problema de otimização convexa com restrições na forma de inequações matriciais lineares (ou no inglês: Linear Matrix Inequalities - LMI). A formulação do problema de otimização parte da teoria de estabilidade segundo Lyapunov com um funcional Lyapunov-Krasoviskii, adição de um custo quadrático, para ajuste de desempenho, e de um critério de desempenho transitório dado pela taxa de decaimento exponencial da norma dos estados. É apresentada a comparação entre as estratégias de controle e a validação do controlador repetitivo proposto aplicado ao caso com linearização perfeita e ao caso com o modelo não linear do manipulador. No primeiro caso, é feita a simulação do modelo linear do manipulador com adição de um torque de atrito na junta. No segundo caso, é utilizado o sistema ROS (Robot Operating System) com o programa Gazebo simulando o manipulador WAM considerando erros de linearização, isto é, incertezas paramétricas. / This work presents a comparison between the strategies of computed-torque control and repetitive control applied to robotic manipulators. The main objective in use these controllers with the manipulator is to tracking periodic trajectory in joint space. The development and implementation of controllers are focused on the Whole Arm Manipulator (WAM) of the Barrett Technology®Inc. Also featured are a non-linear model formulation of the manipulator and the synthesis of controllers for computed-torque control and repetitive control applied to the manipulator model linearized by state feedback. The computed-torque controller is presented in its classic form. For the repetitive controller, the synthesis is based on the internal model principle with the addition of a repetitive structure and a proportional-derivative reference tracking error feedback. The design of the repetitive controller gains is done through a convex optimization problem with linear matrix inequalities (LMI) constraints. The formulation of the optimization problem is based on the Lyapunov stability theory using a Lyapunov-Krasoviskii functional, addition of a quadratic cost for performance adjustment and a transient performance criteria given by the exponential decay rate of the states norm. A comparison between the control strategies and the validation of the repetitive controller applied to the case with perfect linearization and the case with the non-linear model of the manipulator are presented. In the first case, is made simulations of the linear model of the manipulator in MATLAB program, with the addition of a disturbance modeling the friction torque at the joint. In the second case, is used the Robot Operating System (ROS) with Gazebo program simulating the WAM nonlinear model. In this case, a possible mismatch between the model used for the feedback linearization and the real system is taken into account.

Orientadora: Prof. Dra. Elvira Rafikova / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Mecânica, 2017. / Este projeto aborda a aplicação do controle SDRE (State Dependent Ricatti Equation ¿ Equação de Ricatti Dependente de Estado) para controlar a trajetória de um protótipo de Hovercraft. Um Hovercraft é um veículo anfíbio sustentado por um colchão de ar em sua base, fazendo com que este não entre em contato com a superfície terrestre ou aquática. Inicialmente é feito o estudo da modelagem dinâmica desse sistema sendo que se trata de um veículo com restrições não-holonômicas em seus movimentos. São apresentadas algumas técnicas de controle aplicadas para controlar este sistema dinâmico disponíveis na literatura de referência consultada. É discutido o método de controle SDRE bem como é feita a escrita do sistema em espaço de estado de erros (sistema em desvios) garantindo, inclusive, a sua controlabilidade. O objetivo deste trabalho é simular numericamente o comportamento do sistema dinâmico controlado em relação à sua trajetória utilizando a ferramenta Matlab®. São simulados regimes de trajetórias retilíneas acelerada e uniforme, circulares e estabilização em um ponto; variando as condições iniciais do sistema dinâmico do Hovercraft. Além disso, projetou-se e construiu-se um protótipo de Hovercraft para implementar o controle projetado numericamente através do software LabView® comunicando-se com a placa Arduino®. / This project addresses the use of SDRE control (State Dependent Ricatti Equation) to control the trajectory of a Hovercraft prototype. A Hovercraft is an amphibious vehicle sustained on an air cushion at its base, causing it to not contact the land or water surface. Initially, it is made the dynamic modelling analysis of the system considering it is a vehicle with nonholonomic constraints on its movements. Are presented some control techniques applied to control this dynamic system available in the reference literature consulted. The SDRE control method is discussed as well as a system writing in the error state space (system in deviations), including its controllability. The objective of this work is to numerically simulate the behavior of the controlled dynamic system in relation to its trajectory using the software Matlab ®. Straight accelerated and uniform, circular and one-point stabilization regimes are simulated; varying the initial conditions of the Hovercraft. In addition, it is designed and built a Hovercraft prototype to implement numerically the control SDRE through LabView® software communicating with Arduino® board.