2,133 research outputs found

    Learning of Generalized Manipulation Strategies in Service Robotics

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    This thesis makes a contribution to autonomous robotic manipulation. The core is a novel constraint-based representation of manipulation tasks suitable for flexible online motion planning. Interactive learning from natural human demonstrations is combined with parallelized optimization to enable efficient learning of complex manipulation tasks with limited training data. Prior planning results are encoded automatically into the model to reduce planning time and solve the correspondence problem

    Robust Hand Motion Capture and Physics-Based Control for Grasping in Real Time

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    Hand motion capture technologies are being explored due to high demands in the fields such as video game, virtual reality, sign language recognition, human-computer interaction, and robotics. However, existing systems suffer a few limitations, e.g. they are high-cost (expensive capture devices), intrusive (additional wear-on sensors or complex configurations), and restrictive (limited motion varieties and restricted capture space). This dissertation mainly focus on exploring algorithms and applications for the hand motion capture system that is low-cost, non-intrusive, low-restriction, high-accuracy, and robust. More specifically, we develop a realtime and fully-automatic hand tracking system using a low-cost depth camera. We first introduce an efficient shape-indexed cascaded pose regressor that directly estimates 3D hand poses from depth images. A unique property of our hand pose regressor is to utilize a low-dimensional parametric hand geometric model to learn 3D shape-indexed features robust to variations in hand shapes, viewpoints and hand poses. We further introduce a hybrid tracking scheme that effectively complements our hand pose regressor with model-based hand tracking. In addition, we develop a rapid 3D hand shape modeling method that uses a small number of depth images to accurately construct a subject-specific skinned mesh model for hand tracking. This step not only automates the whole tracking system but also improves the robustness and accuracy of model-based tracking and hand pose regression. Additionally, we also propose a physically realistic human grasping synthesis method that is capable to grasp a wide variety of objects. Given an object to be grasped, our method is capable to compute required controls (e.g. forces and torques) that advance the simulation to achieve realistic grasping. Our method combines the power of data-driven synthesis and physics-based grasping control. We first introduce a data-driven method to synthesize a realistic grasping motion from large sets of prerecorded grasping motion data. And then we transform the synthesized kinematic motion to a physically realistic one by utilizing our online physics-based motion control method. In addition, we also provide a performance interface which allows the user to act out before a depth camera to control a virtual object

    Robust Hand Motion Capture and Physics-Based Control for Grasping in Real Time

    Get PDF
    Hand motion capture technologies are being explored due to high demands in the fields such as video game, virtual reality, sign language recognition, human-computer interaction, and robotics. However, existing systems suffer a few limitations, e.g. they are high-cost (expensive capture devices), intrusive (additional wear-on sensors or complex configurations), and restrictive (limited motion varieties and restricted capture space). This dissertation mainly focus on exploring algorithms and applications for the hand motion capture system that is low-cost, non-intrusive, low-restriction, high-accuracy, and robust. More specifically, we develop a realtime and fully-automatic hand tracking system using a low-cost depth camera. We first introduce an efficient shape-indexed cascaded pose regressor that directly estimates 3D hand poses from depth images. A unique property of our hand pose regressor is to utilize a low-dimensional parametric hand geometric model to learn 3D shape-indexed features robust to variations in hand shapes, viewpoints and hand poses. We further introduce a hybrid tracking scheme that effectively complements our hand pose regressor with model-based hand tracking. In addition, we develop a rapid 3D hand shape modeling method that uses a small number of depth images to accurately construct a subject-specific skinned mesh model for hand tracking. This step not only automates the whole tracking system but also improves the robustness and accuracy of model-based tracking and hand pose regression. Additionally, we also propose a physically realistic human grasping synthesis method that is capable to grasp a wide variety of objects. Given an object to be grasped, our method is capable to compute required controls (e.g. forces and torques) that advance the simulation to achieve realistic grasping. Our method combines the power of data-driven synthesis and physics-based grasping control. We first introduce a data-driven method to synthesize a realistic grasping motion from large sets of prerecorded grasping motion data. And then we transform the synthesized kinematic motion to a physically realistic one by utilizing our online physics-based motion control method. In addition, we also provide a performance interface which allows the user to act out before a depth camera to control a virtual object

    Advanced grasping with the Pisa/IIT softHand

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    This chapter presents the hardware, software and overall strategy used by the team UNIPI-IIT-QB to participate to the Robotic Grasping and Manipulation Competition. It relies on the PISA/IIT SoftHand, which is underactuated soft robotic hand that can adapt to the grasped object shape and is compliant with the environment. It was used for the hand-in-hand and for the simulation tracks, where the team reached first and third places respectively

    MĂ©thode interactive et par l'apprentissage pour la generation de trajectoire en conception du produit

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    The accessibility is an important factor considered in the validation and verification phase of the product design and usually dominates the time and costs in this phase. Defining the accessibility verification as the motion planning problem, the sampling based motion planners gained success in the past fifteen years. However, the performances of them are usually shackled by the narrow passage problem arising when complex assemblies are composed of large number of parts, which often leads to scenes with high obstacle densities. Unfortunately, humans’ manual manipulations in the narrow passage always show much more difficulties due to the limitations of the interactive devices or the cognitive ability. Meanwhile, the challenges of analyzing the end users’ response in the design process promote the integration with the direct participation of designers.In order to accelerate the path planning in the narrow passage and find the path complying with user’s preferences, a novel interactive motion planning method is proposed. In this method, the integration with a random retraction process helps reduce the difficulty of manual manipulations in the complex assembly/disassembly tasks and provide local guidance to the sampling based planners. Then a hypothesis is proposed about the correlation between the topological structure of the scenario and the motion path in the narrow passage. The topological structure refers to the medial axis (2D) and curve skeleton (3D) with branches pruned. The correlation runs in an opposite manner to the sampling based method and provide a new perspective to solve the narrow passage problem. The curve matching method is used to explore this correlation and an interactive motion planning framework that can learn from experience is constructed in this thesis. We highlight the performance of our framework on a challenging problem in 2D, in which a non-convex object passes through a cluttered environment filled with randomly shaped and located non-convex obstacles.L'accessibilitéest un facteur important pris en compte dans la validation et la vérification en phase de conception du produit et augmente généralement le temps et les coûts de cette phase. Ce domaine de recherche a eu un regain d’intérêt ces quinze dernières années avec notamment de nouveaux planificateurs de mouvement. Cependant, les performances de ces méthodes sont généralement très faibles lorsque le problème se caractérise par des passages étroits des assemblages complexes composées d'un grand nombre de pièces. Cela conduit souvent àdes scènes àforte densitéd'obstacles. Malheureusement, les manipulations manuelles des humains dans le passage étroit montrent toujours beaucoup de difficultés en raison des limitations des dispositifs interactifs ou la capacitécognitive. Pendant ce temps, les défis de l'analyse de la réponse finale des utilisateurs dans le processus de conception promeut l'intégration avec la participation directe des concepteurs.Afin d'accélérer la planification dans le passage étroit et trouver le chemin le plus conforme aux préférences de l'utilisateur, une nouvelle méthode de planification de mouvement interactif est proposée. Nous avons soulignéla performance de notre algorithme dans certains scénarios difficiles en 2D et 3D environnement.Ensuite, une hypothèse est proposésur la corrélation entre la structure topologique du scénario et la trajectoire dans le passage étroit. La méthode basée sur les courbures est utilisée pour explorer cette corrélation et un cadre de planification de mouvement interactif qui peut apprendre de l'expérience est construit dans cette thèse. Nous soulignons la performance de notre cadre sur un problème difficile en 2D, dans lequel un objet non-convexe passe à travers un environnement encombrérempli d'obstacles non-convexes de forme aléatoire et situés

    Antennas everywhere - from space to undersea - design, optimizations and new techniques for spaceborn, ground based and marine antennas

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    The present dissertation gathers the most significant researches and achievements of its author in the antenna domain. The text is organised in three main parts that are intended to guide the reader through a theoretical and technological excursus on antennas solutions, from space to undersea. Each part aims at showing the answer to each of the following questions, respectively: How a spaceborne antenna shall be? How a ground-based antenna shall be? How a media penetrating antenna shall be? In the frame of a collaboration with the European Space Research and Technology Centre (ESTEC) of the European Space Agency (ESA), the author has been involved, after completing on site (in The Netherlands) his M.Sc. degree in 2011, in a research on the optimisation of the scanning properties of confocal dual reflector antenna systems for spaceborne applications. As part of his permanent assignment, since 2012, as consultant at the ESA’s European Space Operations Centre (ESOC), Germany, the author is responsible of different sustaining and investment projects on existing and new ground antenna terminals for space missions. Some of the projects are presented in this work. Together with the group of electromagnetism of the University La Sapienza of Rome, the author has treated problems related to the electromagnetic deep penetration of lossy media using deep penetrating new antenna solutions. The text is organized into five chapters. Chapter 1 is an introduction and deals with the historical background of modern antennas technologies and layouts and with the fundamental parameters for the analysis of antenna systems related to space and terrestrial contexts. Chapter 2 presents the major achievements of a study on a dual confocal offset antenna configuration for space applications. In particular the optical aberrations caused by the offset arrangement are analysed in order to validate the system introduced as an interesting solution for compact, light and simple payload antennas. Chapter 3 introduces to the world of ground based antennas and provides some interesting hints on a wide range of ground antenna types. Several designing solutions are proposed with the aim of optimizing the desired available gain for the various applications, from the tracking of a space launcher to the communication with spacecraft at the edge of the solar system. An in-depth study is presented on the upgrade of a radio telescope into a ground terminal for the support of deep space missions, addressing to the required versatility of the antenna layouts and to the sustainability of the ground station environment. In Chapter 4, the possibility of achieving the electromagnetic deep penetration of lossy media is analysed. A new design solution, able to generate inhomogeneous waves, similarly to what performed by leaky wave antennas, is introduced. This layout is of extreme interest for its flexibility and for its potentiality of application, as for instance the deep penetration of seawater. Chapter 5 recaps the conclusions of the entire dissertation showing that the world of antennas is much wider than one may think at first sight and innovative solutions are always behind the corner

    Industrial human-robot collaboration: maximizing performance while maintaining safety

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    The goal of this thesis is to maximize performance in collaborative applications, while maintaining safety. For this, assembly workplaces are analyzed, typical tasks identified, and the potential of collaborative robots is elaborated. Current safety regulations are analyzed in order to identify the challenges in safe human-robot collaboration. Different methods are proposed to solve inefficiency in collaborative applications, in particular, intuitive programming of collaborative robots, efficient control with human-in-the-loop constraints, and a hardware solution, the Robotic Airbag.Das Ziel dieser Arbeit ist die Steigerung der Effizienz in kollaborativen Anwendungen, bei gleichzeitiger Einhaltung der Sicherheitsbestimmungen. Dazu werden Montagearbeitsplätze analysiert und das Potenzial kollaborativer Roboter erarbeitet. Aktuelle Sicherheitsvorschriften werden analysiert, um die Herausforderungen einer sicheren Mensch-Roboter-Zusammenarbeit zu identifizieren. Verschiedene Methoden wie intuitive Programmierung von kollaborativen Robotern, eine effiziente Steuerung mit Human-in-the-Loop Beschränkungen und eine Hardwarelösung - der Robotic Airbag - werden präsentiert
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