Robotic manipulation of cloth: mechanical modeling and perception

(Eng) In this work we study various mathematical problems arising from the robotic manipulation of cloth. First, we develop a locking-free continuous model for the physical simulation of inextensible textiles. We present a novel 'finite element' discretization of our inextensibility constraints which results in a unified treatment of triangle and quadrilateral meshings of the cloth. Next, we explain how to incorporate contacts, self-collisions and friction into the equations of motion, so that frictional forces and inextensibility and collision constraints may be integrated implicitly and without any decoupling. We develop an efficient 'active-set' solver tailored to our non-linear problem which takes into account past active constraints to accelerate the resolution of unresolved contacts and moreover can be initialized from any non-necessarily feasible point. Then, we embark ourselves in the empirical validation of the developed model. We record in a laboratory setting --with depth cameras and motion capture systems-- the motions of seven types of textiles (including e.g. cotton, denim and polyester) of various sizes and at different speeds and end up with more than 80 recordings. The scenarios considered are all dynamic and involve rapid shaking and twisting of the textiles, collisions with frictional objects and even strong hits with a long stick. We then, compare the recorded textiles with the simulations given by our inextensible model, and find that on average the mean error is of the order of 1 cm even for the largest sizes (DIN A2) and the most challenging scenarios. Furthermore, we also tackle other problems relevant to robotic cloth manipulation, such as cloth perception and classification of its states. We present a reconstruction algorithm based on Morse theory that proceeds directly from a point-cloud to obtain a cellular decomposition of a surface with or without boundary: the results are a piecewise parametrization of the cloth surface as a union of Morse cells. From the cellular decomposition the topology of the surface can be then deduced immediately. Finally, we study the configuration space of a piece of cloth: since the original state of a piece of cloth is flat, the set of possible states under the inextensible assumption is the set of developable surfaces isometric to a fixed one. We prove that a generic simple, closed, piecewise regular curve in space can be the boundary of only finitely many developable surfaces with nonvanishing mean curvature. Inspired on this result we introduce the dGLI cloth coordinates, a low-dimensional representation of the state of a piece of cloth based on a directional derivative of the Gauss Linking Integral. These coordinates --computed from the position of the cloth's boundary-- allow to distinguish key qualitative changes in folding sequences.(Esp) En este trabajo estudiamos varios problemas matemáticos relacionados con la manipulación robótica de textiles. En primer lugar, desarrollamos un modelo continuo libre de 'locking' para la simulación física de textiles inextensibles. Presentamos una novedosa discretización usando 'elementos finitos' de nuestras restricciones de inextensibilidad resultando en un tratamiento unificado de mallados triangulares y cuadrangulares de la tela. A continuación, explicamos cómo incorporar contactos, autocolisiones y fricción en las ecuaciones de movimiento, de modo que las fuerzas de fricción y las restricciones de inextensibilidad y colisiones puedan integrarse implícitamente y sin ningún desacoplamiento. Desarrollamos un 'solver' de tipo 'conjunto-activo' adaptado a nuestro problema no lineal que tiene en cuenta las restricciones activas pasadas para acelerar la resolución de los contactos no resueltos y, además, puede inicializarse desde cualquier punto no necesariamente factible. Posteriormente, nos embarcamos en la validación empírica del modelo desarrollado. Grabamos en un entorno de laboratorio -con cámaras de profundidad y sistemas de captura de movimiento- los movimientos de siete tipos de textiles (entre los que se incluyen, por ejemplo, algodón, tela vaquera y poliéster) de varios tamaños y a diferentes velocidades, terminando con más de 80 grabaciones. Los escenarios considerados son todos dinámicos e implican sacudidas y torsiones rápidas de los textiles, colisiones con obstáculos e incluso golpes con una varilla cilíndrica. Finalmente, comparamos las grabaciones con las simulaciones dadas por nuestro modelo inextensible, y encontramos que, de media, el error es del orden de 1 cm incluso para las telas más grandes (DIN A2) y los escenarios más complicados. Además, también abordamos otros problemas relevantes para la manipulación robótica de telas, como son la percepción y la clasificación de sus estados. Presentamos un algoritmo de reconstrucción basado en la teoría de Morse que procede directamente de una nube de puntos para obtener una descomposición celular de una superficie con o sin borde: los resultados son una parametrización a trozos de la superficie de la tela como una unión de celdas de Morse. A partir de la descomposición celular puede deducirse inmediatamente la topología de la superficie. Por último, estudiamos el espacio de configuración de un trozo de tela: dado que el estado original de la tela es plano, el conjunto de estados posibles bajo la hipótesis de inextensibilidad es el conjunto de superficies desarrollables isométricas a una fija. Demostramos que una curva genérica simple, cerrada y regular a trozos en el espacio puede ser el borde de un número finito de superficies desarrollables con curvatura media no nula. Inspirándonos en este resultado, introducimos las coordenadas dGLI, una representación de dimensión baja del estado de un pedazo de tela basada en una derivada direccional de la integral de enlazamiento de Gauss. Estas coordenadas -calculadas a partir de la posición del borde de la tela- permiten distinguir cambios cualitativos clave en distintas secuencias de plegado.Postprint (published version

Robotic manipulation of cloth: mechanical modeling and perception

(Eng) In this work we study various mathematical problems arising from the robotic manipulation of cloth. First, we develop a locking-free continuous model for the physical simulation of inextensible textiles. We present a novel 'finite element' discretization of our inextensibility constraints which results in a unified treatment of triangle and quadrilateral meshings of the cloth. Next, we explain how to incorporate contacts, self-collisions and friction into the equations of motion, so that frictional forces and inextensibility and collision constraints may be integrated implicitly and without any decoupling. We develop an efficient 'active-set' solver tailored to our non-linear problem which takes into account past active constraints to accelerate the resolution of unresolved contacts and moreover can be initialized from any non-necessarily feasible point. Then, we embark ourselves in the empirical validation of the developed model. We record in a laboratory setting --with depth cameras and motion capture systems-- the motions of seven types of textiles (including e.g. cotton, denim and polyester) of various sizes and at different speeds and end up with more than 80 recordings. The scenarios considered are all dynamic and involve rapid shaking and twisting of the textiles, collisions with frictional objects and even strong hits with a long stick. We then, compare the recorded textiles with the simulations given by our inextensible model, and find that on average the mean error is of the order of 1 cm even for the largest sizes (DIN A2) and the most challenging scenarios. Furthermore, we also tackle other problems relevant to robotic cloth manipulation, such as cloth perception and classification of its states. We present a reconstruction algorithm based on Morse theory that proceeds directly from a point-cloud to obtain a cellular decomposition of a surface with or without boundary: the results are a piecewise parametrization of the cloth surface as a union of Morse cells. From the cellular decomposition the topology of the surface can be then deduced immediately. Finally, we study the configuration space of a piece of cloth: since the original state of a piece of cloth is flat, the set of possible states under the inextensible assumption is the set of developable surfaces isometric to a fixed one. We prove that a generic simple, closed, piecewise regular curve in space can be the boundary of only finitely many developable surfaces with nonvanishing mean curvature. Inspired on this result we introduce the dGLI cloth coordinates, a low-dimensional representation of the state of a piece of cloth based on a directional derivative of the Gauss Linking Integral. These coordinates --computed from the position of the cloth's boundary-- allow to distinguish key qualitative changes in folding sequences.(Esp) En este trabajo estudiamos varios problemas matemáticos relacionados con la manipulación robótica de textiles. En primer lugar, desarrollamos un modelo continuo libre de 'locking' para la simulación física de textiles inextensibles. Presentamos una novedosa discretización usando 'elementos finitos' de nuestras restricciones de inextensibilidad resultando en un tratamiento unificado de mallados triangulares y cuadrangulares de la tela. A continuación, explicamos cómo incorporar contactos, autocolisiones y fricción en las ecuaciones de movimiento, de modo que las fuerzas de fricción y las restricciones de inextensibilidad y colisiones puedan integrarse implícitamente y sin ningún desacoplamiento. Desarrollamos un 'solver' de tipo 'conjunto-activo' adaptado a nuestro problema no lineal que tiene en cuenta las restricciones activas pasadas para acelerar la resolución de los contactos no resueltos y, además, puede inicializarse desde cualquier punto no necesariamente factible. Posteriormente, nos embarcamos en la validación empírica del modelo desarrollado. Grabamos en un entorno de laboratorio -con cámaras de profundidad y sistemas de captura de movimiento- los movimientos de siete tipos de textiles (entre los que se incluyen, por ejemplo, algodón, tela vaquera y poliéster) de varios tamaños y a diferentes velocidades, terminando con más de 80 grabaciones. Los escenarios considerados son todos dinámicos e implican sacudidas y torsiones rápidas de los textiles, colisiones con obstáculos e incluso golpes con una varilla cilíndrica. Finalmente, comparamos las grabaciones con las simulaciones dadas por nuestro modelo inextensible, y encontramos que, de media, el error es del orden de 1 cm incluso para las telas más grandes (DIN A2) y los escenarios más complicados. Además, también abordamos otros problemas relevantes para la manipulación robótica de telas, como son la percepción y la clasificación de sus estados. Presentamos un algoritmo de reconstrucción basado en la teoría de Morse que procede directamente de una nube de puntos para obtener una descomposición celular de una superficie con o sin borde: los resultados son una parametrización a trozos de la superficie de la tela como una unión de celdas de Morse. A partir de la descomposición celular puede deducirse inmediatamente la topología de la superficie. Por último, estudiamos el espacio de configuración de un trozo de tela: dado que el estado original de la tela es plano, el conjunto de estados posibles bajo la hipótesis de inextensibilidad es el conjunto de superficies desarrollables isométricas a una fija. Demostramos que una curva genérica simple, cerrada y regular a trozos en el espacio puede ser el borde de un número finito de superficies desarrollables con curvatura media no nula. Inspirándonos en este resultado, introducimos las coordenadas dGLI, una representación de dimensión baja del estado de un pedazo de tela basada en una derivada direccional de la integral de enlazamiento de Gauss. Estas coordenadas -calculadas a partir de la posición del borde de la tela- permiten distinguir cambios cualitativos clave en distintas secuencias de plegado

The Road to General Intelligence

Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory. • Details the pragmatic requirements for real-world General Intelligence. • Describes how machine learning fails to meet these requirements. • Provides a philosophical basis for the proposed approach. • Provides mathematical detail for a reference architecture. • Describes a research program intended to address issues of concern in contemporary AI. The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book

From visuomotor control to latent space planning for robot manipulation

Deep visuomotor control is emerging as an active research area for robot manipulation. Recent advances in learning sensory and motor systems in an end-to-end manner have achieved remarkable performance across a range of complex tasks. Nevertheless, a few limitations restrict visuomotor control from being more widely adopted as the de facto choice when facing a manipulation task on a real robotic platform. First, imitation learning-based visuomotor control approaches tend to suffer from the inability to recover from an out-of-distribution state caused by compounding errors. Second, the lack of versatility in task definition limits skill generalisability. Finally, the training data acquisition process and domain transfer are often impractical. In this thesis, individual solutions are proposed to address each of these issues. In the first part, we find policy uncertainty to be an effective indicator of potential failure cases, in which the robot is stuck in out-of-distribution states. On this basis, we introduce a novel uncertainty-based approach to detect potential failure cases and a recovery strategy based on action-conditioned uncertainty predictions. Then, we propose to employ visual dynamics approximation to our model architecture to capture the motion of the robot arm instead of the static scene background, making it possible to learn versatile skill primitives. In the second part, taking inspiration from the recent progress in latent space planning, we propose a gradient-based optimisation method operating within the latent space of a deep generative model for motion planning. Our approach bypasses the traditional computational challenges encountered by established planning algorithms, and has the capability to specify novel constraints easily and handle multiple constraints simultaneously. Moreover, the training data comes from simple random motor-babbling of kinematically feasible robot states. Our real-world experiments further illustrate that our latent space planning approach can handle both open and closed-loop planning in challenging environments such as heavily cluttered or dynamic scenes. This leads to the first, to our knowledge, closed-loop motion planning algorithm that can incorporate novel custom constraints, and lays the foundation for more complex manipulation tasks

Learning by correlation for computer vision applications: from Kernel methods to deep learning

Learning to spot analogies and differences within/across visual categories is an arguably powerful approach in machine learning and pattern recognition which is directly inspired by human cognition. In this thesis, we investigate a variety of approaches which are primarily driven by correlation and tackle several computer vision applications

Prediction and modelling of complex social networks and their evolution.

This thesis focuses on complex social networks in the context of computational approaches for their prediction and modelling. The increasing popularity and advancement of social net- works paired with the availability of social network data enable empirical analysis, inference, prediction and modelling of social patterns. This data-driven approach towards social science is continuously evolving and is crucial for modelling and understanding of human social behaviour including predicting future social interactions for a wide range of applications. The main difference between traditional datasets and network datasets is the presence of the relational components (links) between instances (nodes) of the network. These links and nodes induce intricate local and global patterns, defining the topology of a network. The topology is ever evolving, determining the dynamics of such a networked system. The work presented in this thesis starts with an extensive analysis of three standard network models, in terms of their properties and self-interactions as well as the size and density of the resultant graphs. These crucial analysis and understanding of the main network models are utilised to later develop a comprehensive network simulation framework. A set of novel nature-inspired link prediction approaches are then developed to predict the evolution of networks, based solely on their topologies. Building on top of these approaches, enhanced topological representations of networks are subsequently combined with node characteristics for the purpose of node classification. Finally, the proposed classification methods are extensively evaluated using simulated networks from our network simulation framework as well as two real-world citation networks. The link prediction approaches proposed in this research show that the topology of the network can be further exploited to improve the prediction of future relationships. Moreover, this research demonstrates the potential of blending state-of-the-art Machine Learning techniques with graph theory. To accelerate such advancements in the field of network science, this research also offers an open- source software to provide high-quality synthetic datasets

Mathematical Sensemaking Via Epistemic Games

In this thesis, I study some aspects of how students learn to use math to make sense of physical phenomena. Solving physics problems usually requires dealing with algebraic expressions. That can take the form of reading equations you’re given, manipulating them, or creating them. It’s possible to use equations simply according to formal rules of algebra, but most students also learn to interpret the equations and use the equations as ways to bolster their physical understanding. Here, I report on three years of studying this mathematical sensemaking an introductory physics for life sciences course at the University of Maryland. There are both qualitative and quantitative threads to this work. The qualitative work analyzes a series of problem-solving interviews. First, I use case studies from these interviews to survey the variety of rich cognitive tools students bring to bear on problems around use of algebraic expressions and equations and make observations on potential applications to instruction. Next, I draw a connection between the ontological metaphors students use for equations and the epistemic games they play while solving problems. I show that certain ontological metaphors are used significantly more often in playing certain e-games, and describe the significance of this finding for problem solving. The quantitative thread of this thesis describes how my collaborators and I created and analyzed the Math Epistemic Games Survey, a math concept inventory that studies how students’ uptake of problem-solving strategies such as “check the extreme cases” progressed over the year-long physics course. I show that students on average make little progress on the MEGS over a semester, which suggests that curriculum development in this area has great potential upside. Finally, I test several different methods of analyzing the multiple-choice test data that go beyond counting correct and incorrect answers to extract lessons from the distractors students choose. Using these methods on computer-simulated data and real data from the MEGS, I caution against drawing too-strong conclusions from their results

XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)

[Resumen] Las Jornadas de Automática (JA) son el evento más importante del Comité Español de Automática (CEA), entidad científico-técnica con más de cincuenta años de vida y destinada a la difusión e implantación de la Automática en la sociedad. Este año se celebra la cuadragésima tercera edición de las JA, que constituyen el punto de encuentro de la comunidad de Automática de nuestro país. La presente edición permitirá dar visibilidad a los nuevos retos y resultados del ámbito, y su uso en un gran número de aplicaciones, entre otras, las energías renovables, la bioingeniería o la robótica asistencial. Además de la componente científica, que se ve reflejada en este libro de actas, las JA son un punto de encuentro de las diferentes generaciones de profesores, investigadores y profesionales, incluyendo la componente social que es de vital importancia. Esta edición 2022 de las JA se celebra en Logroño, capital de La Rioja, región mundialmente conocida por la calidad de sus vinos de Denominación de Origen y que ha asumido el desafío de poder ganar competitividad a través de la transformación verde y digital. Pero también por ser la cuna del castellano e impulsar el Valle de la Lengua con la ayuda de las nuevas tecnologías, entre ellas la Automática Inteligente. Los organizadores de estas JA, pertenecientes al Área de Ingeniería de Sistemas y Automática del Departamento de Ingeniería Eléctrica de la Universidad de La Rioja (UR), constituyen un pilar fundamental en el apoyo a la región para el estudio, implementación y difusión de estos retos. Esta edición, la primera en formato íntegramente presencial después de la pandemia de la covid-19, cuenta con más de 200 asistentes y se celebra a caballo entre el Edificio Politécnico de la Escuela Técnica Superior de Ingeniería Industrial y el Monasterio de Yuso situado en San Millán de la Cogolla, dos marcos excepcionales para la realización de las JA. Como parte del programa científico, dos sesiones plenarias harán hincapié, respectivamente, sobre soluciones de control para afrontar los nuevos retos energéticos, y sobre la calidad de los datos para una inteligencia artificial (IA) imparcial y confiable. También, dos mesas redondas debatirán aplicaciones de la IA y la implantación de la tecnología digital en la actividad profesional. Adicionalmente, destacaremos dos clases magistrales alineadas con tecnología de última generación que serán impartidas por profesionales de la empresa. Las JA también van a albergar dos competiciones: CEABOT, con robots humanoides, y el Concurso de Ingeniería de Control, enfocado a UAVs. A todas estas actividades hay que añadir las reuniones de los grupos temáticos de CEA, las exhibiciones de pósteres con las comunicaciones presentadas a las JA y los expositores de las empresas. Por último, durante el evento se va a proceder a la entrega del “Premio Nacional de Automática” (edición 2022) y del “Premio CEA al Talento Femenino en Automática”, patrocinado por el Gobierno de La Rioja (en su primera edición), además de diversos galardones enmarcados dentro de las actividades de los grupos temáticos de CEA. Las actas de las XLIII Jornadas de Automática están formadas por un total de 143 comunicaciones, organizadas en torno a los nueve Grupos Temáticos y a las dos Líneas Estratégicas de CEA. Los trabajos seleccionados han sido sometidos a un proceso de revisión por pares