[pt] Esta dissertação apresenta o desenvolvimento de um controle híbrido de um robô do tipo humanoide Atlas em regime de locomoção estática para a frente. Nos experimentos faz-se uso do ambiente de simulação Gazebo, que permite uma modelagem precisa do robô. O sistema desenvolvido é composto pela modelagem da mecânica do robô, incluindo as equações da dinâmica que permitem o controle das juntas por torque computado, e pela determinação das posições que as juntas devem assumir. Isto é realizado por agentes que utilizam o algoritmo de aprendizado por reforço Q-Learning aproximado para planejar a locomoção do robô. A definição do espaço de estados, que compõe cada agente, difere da cartesiana tradicional e é baseada no conceito de pontos cardeais para estabelecer as direções a serem seguidas até o objetivo e para evitar obstáculos. Esta definição permite o uso de um ambiente simulado reduzido para treinamento, fornecendo aos agentes um conhecimento prévio à aplicação no ambiente real e facilitando, em consequência, a convergência para uma ação dita ótima em poucas iterações. Utilizam-se, no total, três agentes: um para controlar o deslocamento do centro de massa enquanto as duas pernas estão apoiadas ao chão, e outros dois para manter o centro de massa dentro de uma área de tolerância de cada um dos pés na situação em que o robô estiver apoiado com apenas um dos pés no chão. O controle híbrido foi também concebido para reduzir as chances de queda do robô durante a caminhada mediante o uso de uma série de restrições, tanto pelo aprendizado por reforço como pelo modelo da cinemática do robô. A abordagem proposta permite um treinamento eficiente em poucas iterações, produz bons resultados e assegura a integridade do robô. / [en] This dissertation presents the development of a hybrid control for an Atlas humanoid robot moving forward in a static locomotion regime. The Gazebo simulation environment used in the experiments allows a precise modeling of the robot. The developed system consists of the robot mechanics modeling, including dynamical equations that allow the control of joints by computed-torque and the determination of positions the joints should take. This is accomplished by agents that make use of the approximate Q-Learning reinforcement learning algorithm to plan the robot s locomotion. The definition of the state space that makes up each agent differs from the traditional cartesian one and is based on the concept of cardinal points to establish the directions to be followed to the goal and avoid obstacles. This allows the use of a reduced simulated environment for training, providing the agents with prior knowledge to the application in a real environment and facilitating, as a result, convergence to a so-called optimal action in few iterations. Three agents are used: one to control the center of mass displacement when the two legs are poised on the floor and other two for keeping the center of mass within a tolerance range of each of the legs when only one foot is on the ground. In order to reduce the chance of the robot falling down while walking the hybrid control employs a number of constraints, both in the reinforcement learning part and in the robot kinematics model. The proposed approach allows an effective training in few iterations, achieves good results and ensures the integrity of the robot.

Der vorliegende Beitrag stellt einen Entwurf für eine flexible und robuste Steuerungsarchitektur für Roboter- und Fertigungssysteme vor. Dabei wurde versucht ein offenes Konzept zu realisieren, welches einen vereinfachten Engineeringprozess ermöglicht. Hierzu wird innerhalb der Steuerung eine Trennung zwischen einem funktionellen verhaltensbasierten und einem ablauforientierten Modell vorgeschlagen. Dieser Ansatz wird durch die Verwendung von Aktionsprimitiven innerhalb einer hybriden Robotersteuerung ermöglicht. Diese garantieren durch ihre ausgeprägte Modularität eine hohe Flexibilität und Erweiterbarkeit des entstandenen Systems. Im Beitrag wird sowohl der entstandene Entwurf diskutiert als auch eine prototypische objektorientierte Implementierung vorgestellt sowie erste Ergebnisse präsentiert. / This paper presents a framework for a flexible and robust control architecture for robotic systems. The design incorporates an application independent system concept which allows a simplified engineering process. For this purpose a distinction between a functional behavioural and a sequential control system model is proposed. This approach is based on the utilisation of action primitives within a hybrid control architecture. The use of these primitives affords a high level of modularity through increasing flexibility and expandability of the resulting system. In this paper the proposed framework will be discussed as well as a prototypical object-oriented implementation and first results.

In this dissertation, we present several main research thrusts involving thermodynamic stabilization via energy dissipating hybrid controllers and nonlinear control of network systems. Specifically, a novel class of fixed-order, energy-based hybrid controllers is presented as a means for achieving enhanced energy dissipation in Euler-Lagrange, lossless, and dissipative dynamical systems. These dynamic controllers combine a logical switching architecture with continuous dynamics to guarantee that the system plant energy is strictly decreasing across switching. In addition, we construct hybrid dynamic controllers that guarantee that the closed-loop system is consistent with basic thermodynamic principles. In particular, the existence of an entropy function for the closed-loop system is established that satisfies a hybrid Clausius-type inequality. Special cases of energy-based hybrid controllers involving state-dependent switching are described, and the framework is applied to aerospace system models. The overall framework demonstrates that energy-based hybrid resetting controllers provide an extremely efficient mechanism for dissipating energy in nonlinear dynamical systems. Next, we present finite-time coordination controllers for multiagent network systems. Recent technological advances in communications and computation have spurred a broad interest in autonomous, adaptable vehicle formations. Distributed decision-making for coordination of networks of dynamic agents addresses a broad area of applications including cooperative control of unmanned air vehicles, microsatellite clusters, mobile robotics, and congestion control in communication networks. In this part of the dissertation we focus on finite-time consensus protocols for networks of dynamic agents with undirected information flow. The proposed controller architectures are predicated on the recently developed notion of system thermodynamics resulting in thermodynamically consistent continuous controller architectures involving the exchange of information between agents that guarantee that the closed-loop dynamical network is consistent with basic thermodynamic principles.

Der vorliegende Beitrag stellt einen Entwurf für eine flexible und robuste Steuerungsarchitektur für Roboter- und Fertigungssysteme vor. Dabei wurde versucht ein offenes Konzept zu realisieren, welches einen vereinfachten Engineeringprozess ermöglicht. Hierzu wird innerhalb der Steuerung eine Trennung zwischen einem funktionellen verhaltensbasierten und einem ablauforientierten Modell vorgeschlagen. Dieser Ansatz wird durch die Verwendung von Aktionsprimitiven innerhalb einer hybriden Robotersteuerung ermöglicht. Diese garantieren durch ihre ausgeprägte Modularität eine hohe Flexibilität und Erweiterbarkeit des entstandenen Systems. Im Beitrag wird sowohl der entstandene Entwurf diskutiert als auch eine prototypische objektorientierte Implementierung vorgestellt sowie erste Ergebnisse präsentiert. / This paper presents a framework for a flexible and robust control architecture for robotic systems. The design incorporates an application independent system concept which allows a simplified engineering process. For this purpose a distinction between a functional behavioural and a sequential control system model is proposed. This approach is based on the utilisation of action primitives within a hybrid control architecture. The use of these primitives affords a high level of modularity through increasing flexibility and expandability of the resulting system. In this paper the proposed framework will be discussed as well as a prototypical object-oriented implementation and first results.

Die motorischen Fähigkeiten humanoider Roboter werden häufig von antriebsbedingten Nichtlinearitäten und Reibungseffekten negativ beeinflusst. Zur deren Kompensation werden üblicherweise modellbasierte Regelkreise genutzt, die i.d.R. von einer hochfrequenten Signalverarbeitung und mehreren Sensorqualitäten abhängen. Entgegen solch modellbasierten Techniken werden in der vorliegenden Arbeit modellfreie Steuerungsmethoden auf Basis parallel gekoppelter Antriebe entwickelt. Zur Entwicklung und Untersuchung dieser Steuerungsmethoden wird nach der von Pfeifer in seinem Werk “How the body shapes the way we think” beschriebenen synthetischen Methodik vorgegangen. Entgegen modellbasierten Untersuchungen auf Basis von Simulationen stehen bei der synthetischen Methodik empirische Untersuchungen am realen System im Vordergrund. Als Ausgangspunkt dienen konventionelle elektromechanische Antriebe mit deren bekannten leistungseinschränkenden Nichtlinearitäten und Reibungseffekten. Durch die parallele Kopplung mehrerer Antriebe an einem einzelnen Gelenk wird das Spektrum der Steuerungsmöglichkeiten deutlich erweitert. Es zeigt sich, dass (1) durch eine konstante antagonistische Vorspannung das Arbeitsverhalten von konventionellen Proportionalreglern optimiert werden kann, (2) durch dynamische asymmetrische Änderung der Vorspannung Nichtlinearitäten bei niedrigen Geschwindigkeiten ausgeglichen werden können und (3) getriebebedingte Reibungseffekte mit einer phasenverschobenen Pulsmodulation der Steuersignale kompensiert werden können. Weiterhin wird gezeigt, wie die erarbeiteten Steuerungsmethoden auf beliebig viele parallel gekoppelte Antriebe übertragen werden können. Für den praktischen Einsatz der Steuerungsmethoden werden diese in einer hybriden Steuerung zusammengeführt. Diese wird durch eine weitere Funktion, den Energiesparmodus beim Halten statischer Positionen, ergänzt und am humanoiden Roboter Myon implementiert und experimentell evaluiert. / Motor functions of humanoid robots are often negatively influenced by nonlinearities and friction effects of the actuators. The popular means of compensation are control circuits based on modelling, which rely on powerful HF Signal processing and various sensor qualities. In contrast, this thesis develops non-modelling control methods based on parallel coupled actuators. Development and exploration of these control methods follow Pfeifer’s synthetic methodology as described in his work “How the body shapes the way we think”. In contrast to the analysis based on emulation as used in modelling, the synthetic methodology focuses rather on empirical tests within the real system. The present work explores control methods for parallel coupled actuators for use in robot points. It starts from conventional electromechanical actuators with their known power limiting nonlinearities and frictional effects. Linking several parallel coupled actuators to a single joint significantly expands the spectrum of control capabilities. Using two parallel coupled actuators as an example, it is examined to which extent undesirable properties of single actuators can be compensated. The results show that (1) the Performance of conventional proportional controllers can be optimized by a constant antagonistic bias voltage, (2) nonlinearities at low velocities can be balanced out by a dynamic asymmetrical adjustment of the bias, and that (3) gear related frictional effects can be compensated by a phase shifted pulse modulation of the control signals. In addition, it is shown how the developed control methods can be applied to a random number of parallel coupled actuators. For practical use, the various control methods are combined in a hybrid control, which is supplemented by an energy saving mode when maintaining static positions. The hybrid control is being implemented into the humanoid robot Myon and evaluated by experiment.

<div>Powder Bed Fusion Additive Manufacturing enables the fabrication of metal parts with complex geometry and elaborates internal features, the simplication of the assembly process, and the reduction of development time. However, the lack of consis-tent quality hinders its tremendous potential for widespread application in industry. This limits its ability as a viable manufacturing process particularly in the aerospace and medical industries where high quality and repeatability are critical. A variety of defects, which may be initiated during the powder-bed fusion additive manufacturing process, compromise the repeatability, precision, and resulting mechanical properties of the final part. The literature review shows that a non-uniform temperature distribution throughout fabricated layers is a signicant source of the majority of thermal defects. Therefore, the work introduces an online thermography methodology to study temperature distribution, thermal evolution, and thermal specications of the fabricated layers in powder-bed fusion process or any other thermal inherent AM process. This methodology utilizes infrared technique and segmentation image processing to extract the required data about temperature distribution and HAZs of the layer under fabrication. We conducted some primary experiments in the FDM process to leverage the thermography technique and achieve a certain insight to be able to propose a technique to generate a more uniform temperature distribution. These experiments lead to proposing an innovative chessboard scanning strategy called tessellation algorithm, which can generate more uniform temperature distribution and diminish the layer warpage consequently especially throughout the layers with either geometry that is more complex or poses relatively longer dimensions. In the next step, this work develops a new technique in ABAQUS to verify the proposed scanning strategy. This technique simulates temperature distribution throughout a layer printed by chessboard printing patterns in powder-bed fusion process in a fraction of the time taken by current methods in the literature. This technique compares the temperature distribution throughout a designed layer printed by three presented chessboard-scanning patterns, namely, rastering pattern, helical pattern, and tessellation pattern. The results conrm that the tessellation pattern generates more uniform temperature distribution compared with the other two patterns. Further research is in progress to leverage the thermography methodology to verify the simulation technique. It is also pursuing a hybrid closed-loop online monitoring (OM) and control methodology, which bases on the introduced tessellation algorithm and online thermography in this work and Articial Neural Networking (ANN) to generate the most possible uniform temperature distribution within a safe temperature range layer-by-layer.</div>

The topic of this dissertation is the derivation, development, and evaluation of novel hybrid algorithms for process control that use a limited number of measurements and that are suitable to operate in the presence of large amounts of process noise. As an initial step, affine and neural network statistical process models are developed in order to simulate the steady-state system behavior. Such models are vitally important in the evaluation, testing, and improvement of all other process controllers referred to in this work. Afterwards, fuzzy logic controller rules are assimilated into a mathematical characterization of a model that includes the modes and mode transition rules that define a hybrid hierarchical process control. The main processing entity in such framework is a closed-loop control algorithm that performs global and then local optimizations in order to asymptotically reach minimum bias error; this is done while requiring a minimum number of iterations in order to promptly reach a desired operational window. The results of this research are applied to surface mount technology manufacturing-lines yield optimization. This work achieves a practical degree of control over the solder-paste volume deposition in the Stencil Printing Process (SPP). Results show that it is possible to change the operating point of the process by modifying certain machine parameters and even compensate for the difference in height due to change in print direction.

Purdue School of Engineering and Technology, Indianapolis / Powder Bed Fusion Additive Manufacturing enables the fabrication of metal parts with complex geometry and elaborates internal features, the simplification of the assembly process, and the reduction of development time. However, the lack of consistent quality hinders its tremendous potential for widespread application in industry. This limits its ability as a viable manufacturing process particularly in the aerospace and medical industries where high quality and repeatability are critical. A variety of defects, which may be initiated during the powder-bed fusion additive manufacturing process, compromise the repeatability, precision, and resulting mechanical properties of the final part. The literature review shows that a non-uniform temperature distribution throughout fabricated layers is a significant source of the majority of thermal defects. Therefore, the work introduces an online thermography methodology to study temperature distribution, thermal evolution, and thermal specifications of the fabricated layers in powder-bed fusion process or any other thermal inherent AM process. This methodology utilizes infrared technique and segmentation image processing to extract the required data about temperature distribution and HAZs of the layer under fabrication. We conducted some primary experiments in the FDM process to leverage the thermography technique and achieve a certain insight to be able to propose a technique to generate a more uniform temperature distribution. These experiments lead to proposing an innovative chessboard scanning strategy called tessellation algorithm, which can generate more uniform temperature distribution and diminish the layer warpage consequently especially throughout the layers with either geometry that is more complex or poses relatively longer dimensions. In the next step, this work develops a new technique in ABAQUS to verify the proposed scanning strategy. This technique simulates temperature distribution throughout a layer printed by chessboard printing patterns in powder-bed fusion process in a fraction of the time taken by current methods in the literature. This technique compares the temperature distribution throughout a designed layer printed by three presented chessboard-scanning patterns, namely, rastering pattern, helical pattern, and tessellation pattern. The results confirm that the tessellation pattern generates more uniform temperature distribution compared with the other two patterns. Further research is in progress to leverage the thermography methodology to verify the simulation technique. It is also pursuing a hybrid closed-loop online monitoring and control methodology, which bases on the introduced tessellation algorithm and online thermography in this work and Artificial Neural Networking (ANN) to generate the most possible uniform temperature distribution within a safe temperature range layer-by-layer.