Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 97-114).

In many  applications industrial robots perform the same motion  repeatedly. One way of compensating the repetitive part of the error  is by using iterative learning control (ILC). The ILC algorithm  makes use of the measured errors and iteratively calculates a  correction signal that is applied to the system. The main topic of the thesis is to apply an ILC algorithm to a  dynamic system where the controlled variable is not measured. A  remedy for handling this difficulty is to use additional sensors in  combination with signal processing algorithms to obtain estimates of  the controlled variable. A framework for analysis of ILC algorithms  is proposed for the situation when an ILC algorithm uses an estimate  of the controlled variable. This is a relevant research problem in  for example industrial robot applications, where normally only the  motor angular positions are measured while the control objective is  to follow a desired tool path. Additionally, the dynamic model of  the flexible robot structure suffers from uncertainties. The  behaviour when a system having these difficulties is controlled by  an ILC algorithm using measured variables directly is illustrated  experimentally, on both a serial and a parallel robot, and in  simulations of a flexible two-mass model. It is shown that the  correction of the tool-position error is limited by the accuracy of  the robot model. The benefits of estimation-based ILC is illustrated for cases when  fusing measurements of the robot motor angular positions with  measurements from an additional accelerometer mounted on the robot  tool to form a tool-position estimate. Estimation-based ILC is  studied in simulations on a flexible two-mass model and on a  flexible nonlinear two-link robot model, as well as in experiments  on a parallel robot. The results show that it is possible to improve  the tool performance when a tool-position estimate is used in the  ILC algorithm, compared to when the original measurements available  are used directly in the algorithm. Furthermore, the resulting  performance relies on the quality of the estimate, as expected. In the last part of the thesis, some implementation aspects of ILC  are discussed. Since the ILC algorithm involves filtering of signals  over finite-time intervals, often using non-causal filters, it is  important that the boundary effects of the filtering operations are  appropriately handled when implementing the algorithm. It is  illustrated by theoretical analysis and in simulations that the  method of implementation can have large influence over stability and  convergence properties of the algorithm. / Denna avhandling behandlar reglering genom iterativ inlärning, ILC  (från engelskans iterative learning control). Metoden har sitt  ursprung i industrirobottillämpningar där en robot utför samma  rörelse om och om igen. Ett sätt att kompensera för felen är genom  en ILC-algoritm som beräknar en korrektionssignal, som läggs på  systemet i nästa iteration. ILC-algoritmen kan ses som ett  komplement till det befintliga styrsystemet för att förbättra  prestanda. Det problem som särskilt studeras är då en ILC-algoritm appliceras  på ett dynamiskt system där reglerstorheten inte mäts. Ett sätt att  hantera dessa svårigheter är att använda ytterligare sensorer i  kombination med signalbehandlingsalgoritmer för att beräkna en  skattning av reglerstorheten som kan användas i ILC-algoritmen. Ett  ramverk för analys av skattningsbaserad ILC föreslås i avhandlingen.  Problemet är relevant och motiveras utifrån experiment på både en  seriell och en parallel robot. I konventionella robotstyrsystem  mäts endast de enskilda motorpositionerna, medan verktygspositionen  ska följa en önskad bana. Experimentresultat visar att en  ILC-algoritm baserad på motorpositionsfelen kan reducera dessa fel  effektivt. Dock behöver detta inte betyda en förbättrad  verktygsposition, eftersom robotmotorerna styrs mot felaktiga värden  på grund av att modellerna som används för att beräkna dessa  referensbanor inte beskriver den verkliga robotdynamiken helt. Skattningsbaserad ILC studeras både i simulering av en flexibel  tvåmassemodell och en olinjär robotmodell med flexibla leder, och i  experiment på en parallell robot. I studierna sammanvägs  motorpositionsmätningar med mätningar från en accelerometer på  robotverktyget till en skattning av verktygspositionen som används i  ILC-algoritmen. Resultaten visar att det är möjligt att förbättra  verktygspositionen med skattningsbaserad ILC, jämfört med när  motorpositionsmätningarna används direkt i  ILC-algoritmen. Resultatet beror också på skattningskvaliteten, som  förväntat. Slutligen diskuteras några implementeringsaspekter. Alla värden i  uppdateringssignalen läggs på systemet samtidigt, vilket gör det  möjligt att använda icke-kausal filtering där man utnyttjar framtida  signalvärden i filteringen. Detta gör att det är viktigt hur  randeffekterna (början och slutet av signalen) hanteras när man  implementerar ILC-algoritmen. Genom teoretisk analys och  simuleringsexempel illustreras att implementeringsmetoden kan ha  stor betydelse för egenskaperna hos ILC-algoritmen.

O presente trabalho trata da implementação de um sistema de visão robótica para reconhecimento de formas bidimensionais e transformação do contorno em trajetória para um manipulador industrial. A aquisição da imagem ocorre através de uma câmera CCD sobre a área específica de captura. O uso de uma webcam também é testado. A imagem captada é enviada para o computador com processamento realizado em MATLAB, através de rotina de software de controle, escrita em VB.NET. São analisadas variações de contraste e resolução com objetos distintos, onde o sistema identifica os pixels que delimitam o contorno do objeto utilizando limiarização pelo Método de Otsu e algoritmos morfológicos. A posição de cada pixel é processada, transformada em coordenadas cartesianas e enviada para o controle do manipulador robótico, que efetua a trajetória, simulando um processo industrial. A transmissão ao controle do manipulador é realizada em protocolo especial, via porta paralela de um microcomputador à placa de aquisição de sinais digitais do controle do manipulador. Um processo de simulação em uma célula de manufatura proposto para validar o sistema, identifica objetos distintos que chegam de forma desordenada através de uma esteira transportadora. / This work approaches the implementation of a robotics vision system to recognize 2D forms and contour transformation in trajectory to an industrial manipulator. The image acquisition occur by CCD video camera on the specific capture area. A webcam system is also tested. The captured image is sent to a MATLAB computer processing, through a control software routine, written in VB. NET. The contrast and resolution changes are analyzed with different objects where the system identifies the pixels of object contour using Otsu’s Thresholding Method and morphological algorithms. The position of each pixel is processed, transformed in cartesian coordinates and sent to the robotic manipulator control, which executes the trajectory simulating an industrial process. The transmission to the manipulator control is realized in a special protocol, using the parallel port of computer and a digital signal acquisition card of the manipulator control. A simulation process in a manufacturing cell is aimed to validate the system, identifying distinct objects that coming in a disorientated form from a belt conveyor.

O presente trabalho trata da implementação de um sistema de visão robótica para reconhecimento de formas bidimensionais e transformação do contorno em trajetória para um manipulador industrial. A aquisição da imagem ocorre através de uma câmera CCD sobre a área específica de captura. O uso de uma webcam também é testado. A imagem captada é enviada para o computador com processamento realizado em MATLAB, através de rotina de software de controle, escrita em VB.NET. São analisadas variações de contraste e resolução com objetos distintos, onde o sistema identifica os pixels que delimitam o contorno do objeto utilizando limiarização pelo Método de Otsu e algoritmos morfológicos. A posição de cada pixel é processada, transformada em coordenadas cartesianas e enviada para o controle do manipulador robótico, que efetua a trajetória, simulando um processo industrial. A transmissão ao controle do manipulador é realizada em protocolo especial, via porta paralela de um microcomputador à placa de aquisição de sinais digitais do controle do manipulador. Um processo de simulação em uma célula de manufatura proposto para validar o sistema, identifica objetos distintos que chegam de forma desordenada através de uma esteira transportadora. / This work approaches the implementation of a robotics vision system to recognize 2D forms and contour transformation in trajectory to an industrial manipulator. The image acquisition occur by CCD video camera on the specific capture area. A webcam system is also tested. The captured image is sent to a MATLAB computer processing, through a control software routine, written in VB. NET. The contrast and resolution changes are analyzed with different objects where the system identifies the pixels of object contour using Otsu’s Thresholding Method and morphological algorithms. The position of each pixel is processed, transformed in cartesian coordinates and sent to the robotic manipulator control, which executes the trajectory simulating an industrial process. The transmission to the manipulator control is realized in a special protocol, using the parallel port of computer and a digital signal acquisition card of the manipulator control. A simulation process in a manufacturing cell is aimed to validate the system, identifying distinct objects that coming in a disorientated form from a belt conveyor.

O presente trabalho trata da implementação de um sistema de visão robótica para reconhecimento de formas bidimensionais e transformação do contorno em trajetória para um manipulador industrial. A aquisição da imagem ocorre através de uma câmera CCD sobre a área específica de captura. O uso de uma webcam também é testado. A imagem captada é enviada para o computador com processamento realizado em MATLAB, através de rotina de software de controle, escrita em VB.NET. São analisadas variações de contraste e resolução com objetos distintos, onde o sistema identifica os pixels que delimitam o contorno do objeto utilizando limiarização pelo Método de Otsu e algoritmos morfológicos. A posição de cada pixel é processada, transformada em coordenadas cartesianas e enviada para o controle do manipulador robótico, que efetua a trajetória, simulando um processo industrial. A transmissão ao controle do manipulador é realizada em protocolo especial, via porta paralela de um microcomputador à placa de aquisição de sinais digitais do controle do manipulador. Um processo de simulação em uma célula de manufatura proposto para validar o sistema, identifica objetos distintos que chegam de forma desordenada através de uma esteira transportadora. / This work approaches the implementation of a robotics vision system to recognize 2D forms and contour transformation in trajectory to an industrial manipulator. The image acquisition occur by CCD video camera on the specific capture area. A webcam system is also tested. The captured image is sent to a MATLAB computer processing, through a control software routine, written in VB. NET. The contrast and resolution changes are analyzed with different objects where the system identifies the pixels of object contour using Otsu’s Thresholding Method and morphological algorithms. The position of each pixel is processed, transformed in cartesian coordinates and sent to the robotic manipulator control, which executes the trajectory simulating an industrial process. The transmission to the manipulator control is realized in a special protocol, using the parallel port of computer and a digital signal acquisition card of the manipulator control. A simulation process in a manufacturing cell is aimed to validate the system, identifying distinct objects that coming in a disorientated form from a belt conveyor.

L'arrivée simultanée de capteurs de profondeur et couleur, et d'algorithmes de détection de squelettes super-temps-réel a conduit à un regain de la recherche sur la capture de mouvements humains. Cette fonctionnalité constitue un point clé de la communication Homme-Machine. Mais le contexte d'application de ces dernières avancées est l'interaction volontaire et fronto-parallèle, ce qui permet certaines approximations et requiert un positionnement spécifique des capteurs. Dans cette thèse, nous présentons une approche multi-capteurs, conçue pour améliorer la robustesse et la précision du positionnement des articulations de l'homme, et fondée sur un processus de lissage trajectoriel par intégration temporelle, et le filtrage des squelettes détectés par chaque capteur. L'approche est testée sur une base de données nouvelle acquise spécifiquement, avec une méthodologie d'étalonnage adaptée spécialement. Un début d'extension à la perception jointe avec du contexte, ici des objets, est proposée. / Simultaneous apparition of depth and color sensors and super-realtime skeleton detection algorithms led to a surge of new research in Human Motion Capture. This feature is a key part of Human-Machine Interaction. But the applicative context of those new technologies is voluntary, fronto-parallel interaction with the sensor, which allowed the designers certain approximations and requires a specific sensor placement. In this thesis, we present a multi-sensor approach, designed to improve robustness and accuracy of a human's joints positionning, and based on a trajectory smoothing process by temporal integration, and filtering of the skeletons detected in each sensor. The approach has been tested on a new specially constituted database, with a specifically adapted calibration methodology. We also began extending the approach to context-based improvements, with object perception being proposed.

L’utilisation de robots collaboratifs dans l’industrie de production est en plein essor. Ces robots, dont la puissance est limitée, sont dotés de capteurs leur permettant de détecter la présence d’obstacles, afin de garantir la sécurité des humains se trouvant aux alentours. On s’intéresse dans cette thèse à l’utilisation de systèmes redondants, collaboratifs et mobiles (bras articulés montés sur plateformes mobiles), dans un environnement de production aéronautique peuplé d’humains, pour la réalisation d’opérations d’assemblage. Du point de vue des process, l’utilisation de ces systèmes, souvent beaucoup moins imposants et rigides que leurs homologues non collaboratifs, est jalonnée de défis. La grande souplesse mécanique et les faibles couples qui les caractérisent peuvent induire des imprécisions de positionnement et une incapacité à soutenir l’intensité d’une interaction physique. Ce contexte induit également un besoin d’autonomie de ces systèmes, qui sont amenés à travailler dans des environnements en perpétuelle évolution. Dans cette thèse, une formulation de la redondance cinématique est d’abord présentée. Le formalisme associé permet de simplifier l’exploitation de la liberté que ces systèmes possèdent sur le choix des postures à utiliser pour réaliser des tâches de placement statique de l’effecteur. Ce formalisme est ensuite exploité pour améliorer et caractériser le comportement en déformation et la capacité d’application d’efforts des systèmes redondants sériels. Enfin, le sujet de la planification des mouvements de systèmes robotisés dans un environnement dynamique et encombré est considéré. La solution présentée adapte l’algorithme bien connu des Probabilistic RoadMaps pour y inclure une anticipation des trajectoires des obstacles dynamiques. Cette solution permet de planifier des mouvements sécuritaires, peu intrusifs et efficaces, jusqu’à la destination. / Industrial applications involving collaborative robots are regarded with a growing interest. These power-limited systems are embedded with additional sensing capabilities, which allow them to safely work around humans and conquer new industrial grounds. The subject of managing redundant, collaborative and mobile systems, for assembly operations within a human-populated aircraft production environment, is addressed in this thesis. From a process perspective, the use of these smaller and less stiff counterparts of the non-collaborative robots comes with new challenges. Their high mechanical flexibility and weak actuation can cause shortcomings in positioning accuracy or for interaction force sustainment. The ever-changing nature of human-populated environments also requires highly autonomous solutions. In this thesis, a formulation of positional redundancy is presented. It aims at simplifying the exploitation of the freedom redundant manipulators have on static-task-fulfilling postures. The associated formalism is then exploited to characterise and improve the deformational behaviour and the force capacity of redundant serial systems. Finally, the subject of planning motions within cluttered and dynamic environments is addressed. An adaptation of the well-known Probabilistic RoadMaps method is presented – to which obstacles trajectories anticipation has been included. This solution allows to plan safe, efficient and non-intrusive motions to a given destination.

This diploma thesis is focused on the design of a robotic workplace for arc welding and its subsequent virtual commissioning. The summary deals with knowledge from industrial robotics and arc welding, the system analysis is focused on the composition of the workplace and the principle of arc welding, including acting influences. In the practical part, several variants of the solution are proposed, the most suitable variant is processed in the form of a 3D model. This model is then simulated, including all processes, a control program is created, and virtual commissioning of the workplace is demonstrated.

Collaborative robots are becoming more commonplace within factories to work alongside their human counterparts. With this newfound perspective towards robots being seen as collaborative partners comes the question of how interacting with these machines will change. This thesis therefore focuses on investigating the connection between facial expression communication in industrial robots and users' perceptions. Experiments were conducted to investigate the relationship between users' perceptions towards both existing facial expressions of the Baxter robot (an industrial robot by Rethink Robotics) and redesigned versions of these facial expressions. Findings reveal that the redesigned facial expressions provide a better match to users’ expectations. In addition, insights into improving the expressive communication between humans and robots are discussed, including the need for additional solutions which can complement the facial expressions displayed by providing more detailed information as needed. The last section of this thesis presents future research directions towards building a more intuitive and user-friendly human-robot cooperation space for future industrial robots.

In the context of Industry 4.0, the prominence of robotics has grown significantly, leading to a pressing need for advanced monitoring techniques. This thesis explores the potential role of Mixed Reality (MR) in robot condition monitoring through an exhaustive literature review of 138 selected studies. The investigation showed prevalent methods in robot condition monitoring, such as Fault Detection and Diagnosis, Machine Learning Techniques, Signal-based Monitoring, Model-based Monitoring, and Real-time Monitoring. MR, while not yet abundant in this context, is emerging as a promising tool, especially for real-time data visualization, remote maintenance, and integration with other technologies. By visually representing data and predictions directly on the robot, MR can speed up the diagnostic process, improve safety, and promote remote collaboration. However, challenges such as integration with legacy systems, effective data management, and hardware limitations were identified. The research also observed trends, benefits, and challenges in the broader application of MR in industrial settings. While MR offers significant advantages, including enhanced visualization, improved efficiency, and cost savings, its full integration into the world of robot condition monitoring necessitates further research and iterative refinement. In essence, this thesis presents a balanced overview of the potential and challenges of MR in robot condition monitoring, setting the stage for future exploration in this burgeoning domain.