none ; With this sentence from his Metaphysica, Aristotle perfectly introduces us to the importance of eyesight for humans, as well as for any advanced living being. Since, to a large extent, robotics is concerned with the emulation of human skills in an artificial context, a natural requirement is to cope with vision for a full interaction with the world. In this respect, this Thesis explores the problem of exploiting visual information to control the motion of robotic systems equipped with onboard cameras. We build our proposals upon the Visual Servoing paradigm, which bridges Computer Vision (image processing, scene interpretation, feature extraction, etc.) with topics proper to the Control Theory field. Indeed, within Visual Servoing, a camera is modeled as a nonlinear function of the scene, i.e., of 3D states subject to rigid body kinematics. Therefore, visual pose control reduces to a problem of output regulation, or task realization if we conform to the robotic nomenclature. Once this view is adopted, any task realization algorithm can be used to fulfill a visual task, and, more in general, the problem can be tackled with the tools of Control Theory. In order to fully exploit this formulation, however, a suitable task-oriented modeling of robot manipulators is required. Therefore, in the first part of the Thesis, we develop a theoretical framework for kinematic modeling and control of such systems. While keeping the treatment at the most general level, we place some emphasis on the cases of fixed and nonholonomic mobile manipulators. Indeed, the former class is ubiquitous in robotics, and the latter conveniently merges dexterity with extended ( unlimited) workspace capabilities. A special attention is also devoted to the exploitation of possible redundancy with respect to a given task, in terms of both improvement of overall performance, and satisfaction of secondary constraints. Such modeling framework is then combined with the schemes proper to Visual Servoing to obtain a unique formulation for visual ...


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    Title :

    Visual Estimation and Control of Robot Manipulating Systems



    Publication date :

    2016-12-16


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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