229 research outputs found

    Design of decorative 3D models: from geodesic ornaments to tangible assemblies

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    L'obiettivo di questa tesi è sviluppare strumenti utili per creare opere d'arte decorative digitali in 3D. Uno dei processi decorativi più comunemente usati prevede la creazione di pattern decorativi, al fine di abbellire gli oggetti. Questi pattern possono essere dipinti sull'oggetto di base o realizzati con l'applicazione di piccoli elementi decorativi. Tuttavia, la loro realizzazione nei media digitali non è banale. Da un lato, gli utenti esperti possono eseguire manualmente la pittura delle texture o scolpire ogni decorazione, ma questo processo può richiedere ore per produrre un singolo pezzo e deve essere ripetuto da zero per ogni modello da decorare. D'altra parte, gli approcci automatici allo stato dell'arte si basano sull'approssimazione di questi processi con texturing basato su esempi o texturing procedurale, o con sistemi di riproiezione 3D. Tuttavia, questi approcci possono introdurre importanti limiti nei modelli utilizzabili e nella qualità dei risultati. Il nostro lavoro sfrutta invece i recenti progressi e miglioramenti delle prestazioni nel campo dell'elaborazione geometrica per creare modelli decorativi direttamente sulle superfici. Presentiamo una pipeline per i pattern 2D e una per quelli 3D, e dimostriamo come ognuna di esse possa ricreare una vasta gamma di risultati con minime modifiche dei parametri. Inoltre, studiamo la possibilità di creare modelli decorativi tangibili. I pattern 3D generati possono essere stampati in 3D e applicati a oggetti realmente esistenti precedentemente scansionati. Discutiamo anche la creazione di modelli con mattoncini da costruzione, e la possibilità di mescolare mattoncini standard e mattoncini custom stampati in 3D. Ciò consente una rappresentazione precisa indipendentemente da quanto la voxelizzazione sia approssimativa. I principali contributi di questa tesi sono l'implementazione di due diverse pipeline decorative, un approccio euristico alla costruzione con mattoncini e un dataset per testare quest'ultimo.The aim of this thesis is to develop effective tools to create digital decorative 3D artworks. Real-world art often involves the use of decorative patterns to enrich objects. These patterns can be painted on the base or might be realized with the application of small decorative elements. However, their creation in digital media is not trivial. On the one hand, users can manually perform texture paint or sculpt each decoration, in a process that can take hours to produce a single piece and needs to be repeated from the ground up for every model that needs to be decorated. On the other hand, automatic approaches in state of the art rely on approximating these processes with procedural or by-example texturing or with 3D reprojection. However, these approaches can introduce significant limitations in the models that can be used and in the quality of the results. Instead, our work exploits the recent advances and performance improvements in the geometry processing field to create decorative patterns directly on surfaces. We present a pipeline for 2D and one for 3D patterns and demonstrate how each of them can recreate a variety of results with minimal tweaking of the parameters. Furthermore, we investigate the possibility of creating decorative tangible models. The 3D patterns we generate can be 3D printed and applied to previously scanned real-world objects. We also discuss the creation of models with standard building bricks and the possibility of mixing standard and custom 3D-printed bricks. This allows for a precise representation regardless of the coarseness of the voxelization. The main contributions of this thesis are the implementation of two different decorative pipelines, a heuristic approach to brick construction, and a dataset to test the latter

    DESIGN AND VERIFICATION OF AUTONOMOUS SYSTEMS IN THE PRESENCE OF UNCERTAINTIES

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    Autonomous Systems offer hope towards moving away from mechanized, unsafe, manual, often inefficient practices. The last decade has seen several small, but important, steps towards making this dream into reality. These advancements have helped us to achieve limited autonomy in several places, such as, driving, factory floors, surgeries, wearables, and home assistants, etc. Nevertheless, autonomous systems are required to operate in a wide range of environments with uncertainties (viz., sensor errors, timing errors, dynamic nature of the environment, etc.). Such environmental uncertainties, even when present in small amounts, can have drastic impact on the safety of the system—thus hampering the goal of achieving higher degree of autonomy, especially in safety critical domains. To this end, the dissertation shall discuss formaltechniques that are able to verify and design autonomous systems for safety, even under the presence of such uncertainties, allowing for their trustworthy deployment in the real world. Specifically, the dissertation shall discuss monitoring techniques for autonomous systems from available (noisy) logs, and safety-verification techniques of autonomous system controllers under timing uncertainties. Secondly, using heterogeneous learning-based cloud computing models that can balance uncertainty in output and computation cost, the dissertation will present techniques for designing safe and performance-optimal autonomous systems.Doctor of Philosoph

    Safe Deep Reinforcement Learning: Enhancing the Reliability of Intelligent Systems

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    In the last few years, the impressive success of deep reinforcement learning (DRL) agents in a wide variety of applications has led to the adoption of these systems in safety-critical contexts (e.g., autonomous driving, robotics, and medical applications), where expensive hardware and human safety can be involved. In such contexts, an intelligent learning agent must adhere to certain requirements that go beyond the simple accomplishment of the task and typically include constraints on the agent's behavior. Against this background, this thesis proposes a set of training and validation methodologies that constitute a unified pipeline to generate safe and reliable DRL agents. In the first part of this dissertation, we focus on the problem of constrained DRL, leaving the challenging problem of the formal verification of deep neural networks for the second part of this work. As humans, in our growing process, the help of a mentor is crucial to learn effective strategies to solve a problem while a learning process driven only by a trial-and-error approach usually leads to unsafe and inefficient solutions. Similarly, a pure end-to-end deep reinforcement learning approach often results in suboptimal policies, which typically translates into unpredictable, and thus unreliable, behaviors. Following this intuition, we propose to impose a set of constraints into the DRL loop to guide the training process. These requirements, which typically encode domain expert knowledge, can be seen as suggestions that the agent should follow but is allowed to sometimes ignore if useful to maximize the reward signal. A foundational requirement for our work is finding a proper strategy to define and formally encode these constraints (which we refer to as \textit{rules}). In this thesis, we propose to exploit a formal language inherited from the software engineering community: scenario-based programming (SBP). For the actual training, we rely on the constrained reinforcement learning paradigm, proposing an extended version of the Lagrangian PPO algorithm. Recalling the parallelism with human beings, before being authorized to perform safety-critical operations, we must obtain a certification (e.g., a license to drive a car or a degree to perform medical operations). In the second part of this dissertation, we apply this concept in a deep reinforcement learning context, where the intelligent agents are controlled by artificial neural networks. In particular, we propose to perform a model selection phase after the training to find models that formally respect some given safety requirements before the deployment. However, DNNs have long been considered unpredictable black boxes and thus unsuitable for safety-critical contexts. Against this background, we build upon the emerging field of formal verification for neural networks to extend state-of-the-art approaches to robotic decision-making contexts. We propose ``ProVe", a verification tool for decision-making DNNs that quantifies the probability of violating the specified requirements. In the last chapter of this thesis, we provide a complete case study on a popular robotic problem: ``mapless navigation". Here, we show a concrete example of the application of our pipeline, starting from the definition of the requirements to the training and the final formal verification phase, to finally obtain a provably safe and effective agent

    Robotic manipulation of cloth: mechanical modeling and perception

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    (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

    Autonomous Spacecraft Rendezvous using Tube-based Model Predictive Control: Design and Application

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    As the concentration of large space debris increases, how rendezvous maneuvers involving these typically non-cooperative, freely-tumbling bodies are planned and executed is evolving. The rendezvous must be carefully planned, employing up-to-date in situ data to identify the inertial and motion parameters of the target body, and executed in a manner which accounts for the remaining uncertainty in these parameters. This paper presents an extension of the TRACE pipeline used in the ROAM/TumbleDock Astrobee experiment campaign, which sequences the target state estimation, motion planning, controller design, and maneuver execution tasks while additionally providing logical loop-back avenues to previous tasks, increasing the chances of a successful maneuver. The pipeline’s performance is analyzed in simulation, utilizing: target state estimates generated in a previous activity on a dedicated on-ground testbed; online motion planning, based on non-linear programming and warm-started using a trajectory library generated offline with a novel GPU-based method; and Tube-based Model Predictive Control to robustly track the planned trajectory. Tube-based Model Predictive Control is an actively evolving subject, distributed over multiple publications and various research interests. The necessary theory and considerations for practical implementation of the method are consolidated; its use, features, and limitations in the proposed task are demonstrated

    Robotic manipulation of cloth: mechanical modeling and perception

    Get PDF
    (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

    LIPIcs, Volume 244, ESA 2022, Complete Volume

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    LIPIcs, Volume 244, ESA 2022, Complete Volum

    Multi-Agent Pathfinding in Mixed Discrete-Continuous Time and Space

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    In the multi-agent pathfinding (MAPF) problem, agents must move from their current locations to their individual destinations while avoiding collisions. Ideally, agents move to their destinations as quickly and efficiently as possible. MAPF has many real-world applications such as navigation, warehouse automation, package delivery and games. Coordination of agents is necessary in order to avoid conflicts, however, it can be very computationally expensive to find mutually conflict-free paths for multiple agents – especially as the number of agents is increased. Existing state-ofthe- art algorithms have been focused on simplified problems on grids where agents have no shape or volume, and each action executed by the agents have the same duration, resulting in simplified collision detection and synchronous, timed execution. In the real world agents have a shape, and usually execute actions with variable duration. This thesis re-formulates the MAPF problem definition for continuous actions, designates specific techniques for continuous-time collision detection, re-formulates two popular algorithms for continuous actions and formulates a new algorithm called Conflict-Based Increasing Cost Search (CBICS) for continuous actions
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