589 research outputs found

    Noise-in, Bias-out: Balanced and Real-time MoCap Solving

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    Real-time optical Motion Capture (MoCap) systems have not benefited from the advances in modern data-driven modeling. In this work we apply machine learning to solve noisy unstructured marker estimates in real-time and deliver robust marker-based MoCap even when using sparse affordable sensors. To achieve this we focus on a number of challenges related to model training, namely the sourcing of training data and their long-tailed distribution. Leveraging representation learning we design a technique for imbalanced regression that requires no additional data or labels and improves the performance of our model in rare and challenging poses. By relying on a unified representation, we show that training such a model is not bound to high-end MoCap training data acquisition, and exploit the advances in marker-less MoCap to acquire the necessary data. Finally, we take a step towards richer and affordable MoCap by adapting a body model-based inverse kinematics solution to account for measurement and inference uncertainty, further improving performance and robustness. Project page: https://moverseai.github.io/noise-tailComment: Project page: https://moverseai.github.io/noise-tai

    Leaf Venation Networks

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    Reconstruction and recognition of confusable models using three-dimensional perception

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    Perception is one of the key topics in robotics research. It is about the processing of external sensor data and its interpretation. The necessity of fully autonomous robots makes it crucial to help them to perform tasks more reliably, flexibly, and efficiently. As these platforms obtain more refined manipulation capabilities, they also require expressive and comprehensive environment models: for manipulation and affordance purposes, their models have to involve each one of the objects present in the world, coincidentally with their location, pose, shape and other aspects. The aim of this dissertation is to provide a solution to several of these challenges that arise when meeting the object grasping problem, with the aim of improving the autonomy of the mobile manipulator robot MANFRED-2. By the analysis and interpretation of 3D perception, this thesis covers in the first place the localization of supporting planes in the scenario. As the environment will contain many other things apart from the planar surface, the problem within cluttered scenarios has been solved by means of Differential Evolution, which is a particlebased evolutionary algorithm that evolves in time to the solution that yields the cost function lowest value. Since the final purpose of this thesis is to provide with valuable information for grasping applications, a complete model reconstructor has been developed. The proposed method holdsmany features such as robustness against abrupt rotations, multi-dimensional optimization, feature extensibility, compatible with other scan matching techniques, management of uncertain information and an initialization process to reduce convergence timings. It has been designed using a evolutionarybased scan matching optimizer that takes into account surface features of the object, global form and also texture and color information. The last tackled challenge regards the recognition problem. In order to procure with worthy information about the environment to the robot, a meta classifier that discerns efficiently the observed objects has been implemented. It is capable of distinguishing between confusable objects, such as mugs or dishes with similar shapes but different size or color. The contributions presented in this thesis have been fully implemented and empirically evaluated in the platform. A continuous grasping pipeline covering from perception to grasp planning including visual object recognition for confusable objects has been developed. For that purpose, an indoor environment with several objects on a table is presented in the nearby of the robot. Items are recognized from a database and, if one is chosen, the robot will calculate how to grasp it taking into account the kinematic restrictions associated to the anthropomorphic hand and the 3D model for this particular object. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------La percepción es uno de los temas más relevantes en el mundo de la investigaci ón en robótica. Su objetivo es procesar e interpretar los datos recibidos por un sensor externo. La gran necesidad de desarrollar robots autónomos hace imprescindible proporcionar soluciones que les permita realizar tareas más precisas, flexibles y eficientes. Dado que estas plataformas cada día adquieren mejores capacidades para manipular objetos, también necesitarán modelos expresivos y comprensivos: para realizar tareas de manipulación y prensión, sus modelos han de tener en cuenta cada uno de los objetos presentes en su entorno, junto con su localizaci ón, orientación, forma y otros aspectos. El objeto de la presente tesis doctoral es proponer soluciones a varios de los retos que surgen al enfrentarse al problema del agarre, con el propósito final de aumentar la capacidad de autonomía del robot manipulador MANFRED-2. Mediante el análisis e interpretación de la percepción tridimensional, esta tesis cubre en primer lugar la localización de planos de soporte en sus alrededores. Dado que el entorno contendrá muchos otros elementos aparte de la superficie de apoyo buscada, el problema en entornos abarrotados ha sido solucionado mediante Evolución Diferencial, que es un algoritmo evolutivo basado en partículas que evoluciona temporalmente a la solución que contempla el menor resultado en la función de coste. Puesto que el propósito final de este trabajo de investigación es proveer de información valiosa a las aplicaciones de prensión, se ha desarrollado un reconstructor de modelos completos. El método propuesto posee diferentes características como robustez a giros abruptos, optimización multidimensional, extensión a otras características, compatibilidad con otras técnicas de reconstrucción, manejo de incertidumbres y un proceso de inicialización para reducir el tiempo de convergencia. Ha sido diseñado usando un registro optimizado mediante técnicas evolutivas que tienen en cuenta las particularidades de la superficie del objeto, su forma global y la información relativa a la textura. El último problema abordado está relacionado con el reconocimiento de objetos. Con la intención de abastecer al robot con la mayor información posible sobre el entorno, se ha implementado un meta clasificador que diferencia de manera eficaz los objetos observados. Ha sido capacitado para distinguir objetos confundibles como tazas o platos con formas similares pero con diferentes colores o tamaños. Las contribuciones presentes en esta tesis han sido completamente implementadas y probadas de manera empírica en la plataforma. Se ha desarrollado un sistema que cubre el problema de agarre desde la percepción al cálculo de la trayectoria incluyendo el sistema de reconocimiento de objetos confundibles. Para ello, se ha presentado una mesa con objetos en un entorno cerrado cercano al robot. Los elementos son comparados con una base de datos y si se desea agarrar uno de ellos, el robot estimará cómo cogerlo teniendo en cuenta las restricciones cinemáticas asociadas a una mano antropomórfica y el modelo tridimensional generado del objeto en cuestión

    Quantitative Perspectives on Fifty Years of the Journal of the History of Biology

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    Journal of the History of Biology provides a fifty-year long record for examining the evolution of the history of biology as a scholarly discipline. In this paper, we present a new dataset and preliminary quantitative analysis of the thematic content of JHB from the perspectives of geography, organisms, and thematic fields. The geographic diversity of authors whose work appears in JHB has increased steadily since 1968, but the geographic coverage of the content of JHB articles remains strongly lopsided toward the United States, United Kingdom, and western Europe and has diversified much less dramatically over time. The taxonomic diversity of organisms discussed in JHB increased steadily between 1968 and the late 1990s but declined in later years, mirroring broader patterns of diversification previously reported in the biomedical research literature. Finally, we used a combination of topic modeling and nonlinear dimensionality reduction techniques to develop a model of multi-article fields within JHB. We found evidence for directional changes in the representation of fields on multiple scales. The diversity of JHB with regard to the representation of thematic fields has increased overall, with most of that diversification occurring in recent years. Drawing on the dataset generated in the course of this analysis, as well as web services in the emerging digital history and philosophy of science ecosystem, we have developed an interactive web platform for exploring the content of JHB, and we provide a brief overview of the platform in this article. As a whole, the data and analyses presented here provide a starting-place for further critical reflection on the evolution of the history of biology over the past half-century.Comment: 45 pages, 14 figures, 4 table

    Information Theory and Its Application in Machine Condition Monitoring

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    Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries

    Image similarity in medical images

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    Image similarity in medical images

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    Recent experiments have indicated a strong influence of the substrate grain orientation on the self-ordering in anodic porous alumina. Anodic porous alumina with straight pore channels grown in a stable, self-ordered manner is formed on (001) oriented Al grain, while disordered porous pattern is formed on (101) oriented Al grain with tilted pore channels growing in an unstable manner. In this work, numerical simulation of the pore growth process is carried out to understand this phenomenon. The rate-determining step of the oxide growth is assumed to be the Cabrera-Mott barrier at the oxide/electrolyte (o/e) interface, while the substrate is assumed to determine the ratio β between the ionization and oxidation reactions at the metal/oxide (m/o) interface. By numerically solving the electric field inside a growing porous alumina during anodization, the migration rates of the ions and hence the evolution of the o/e and m/o interfaces are computed. The simulated results show that pore growth is more stable when β is higher. A higher β corresponds to more Al ionized and migrating away from the m/o interface rather than being oxidized, and hence a higher retained O:Al ratio in the oxide. Experimentally measured oxygen content in the self-ordered porous alumina on (001) Al is indeed found to be about 3% higher than that in the disordered alumina on (101) Al, in agreement with the theoretical prediction. The results, therefore, suggest that ionization on (001) Al substrate is relatively easier than on (101) Al, and this leads to the more stable growth of the pore channels on (001) Al

    Phase transitions of Integrated Information in the Generalized Ising Model of the Brain

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    The bold framework of the Integrated Information Theory of consciousness are explored in this thesis in the context of the generalized Ising model of the brain. Small 5-node networks are simulated on the Ising model with Metropolis transitions where the fitting parameter T is fit to empirical functional connectivity matrices of healthy human subjects. Fitting to criticality, results indicate that integrated information undergoes a phase transition at the critical temperature Tc. The results are interpreted in the context of an emerging perspective of the science of complexity and perhaps even the philosophy of science; the universe as a self-organizing critical system undergoing cascades of phase transitions into complexity
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