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Titlebook: Learning-Based Robot Vision; Principles and Appli Josef Pauli Book 2001 Springer-Verlag Berlin Heidelberg 2001 Computer vision.algorithmic

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書目名稱Learning-Based Robot Vision
副標(biāo)題Principles and Appli
編輯Josef Pauli
視頻videohttp://file.papertrans.cn/584/583053/583053.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Learning-Based Robot Vision; Principles and Appli Josef Pauli Book 2001 Springer-Verlag Berlin Heidelberg 2001 Computer vision.algorithmic
描述Industrial robots carry out simple tasks in customized environments for which it is typical that nearly all e?ector movements can be planned during an - line phase. A continual control based on sensory feedback is at most necessary at e?ector positions near target locations utilizing torque or haptic sensors. It is desirable to develop new-generation robots showing higher degrees of autonomy for solving high-level deliberate tasks in natural and dynamic en- ronments. Obviously, camera-equipped robot systems, which take and process images and make use of the visual data, can solve more sophisticated robotic tasks. The development of a (semi-) autonomous camera-equipped robot must be grounded on an infrastructure, based on which the system can acquire and/or adapt task-relevant competences autonomously. This infrastructure consists of technical equipment to support the presentation of real world training samples, various learning mechanisms for automatically acquiring function approximations, and testing methods for evaluating the quality of the learned functions. Accordingly, to develop autonomous camera-equipped robot systems one must ?rst demonstrate relevant objects, critical sit
出版日期Book 2001
關(guān)鍵詞Computer vision; algorithmic learning; autonom; autonomous agents; camera-equiped robots; cognitive syste
版次1
doihttps://doi.org/10.1007/3-540-45124-2
isbn_softcover978-3-540-42108-5
isbn_ebook978-3-540-45124-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2001
The information of publication is updating

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https://doi.org/10.1007/3-540-45124-2Computer vision; algorithmic learning; autonom; autonomous agents; camera-equiped robots; cognitive syste
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Manifolds for Object and Situation Recognition,This chapter presents a generic approach for learning operators for object recognition or situation scoring, which is based on constructing feature manifolds.
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Summary and Discussion,We presented a paradigm of developing camera-equipped robot systems for high-level Robot Vision tasks. The final chapter summarizes and discusses the work.
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