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The "hand-eye-brain" system of intel...
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Qiao, Hong.
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The "hand-eye-brain" system of intelligent robot = from interdisciplinary perspective of information science and neuroscience /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The "hand-eye-brain" system of intelligent robot/ by Hong Qiao, Chao Ma, Rui Li.
其他題名:
from interdisciplinary perspective of information science and neuroscience /
作者:
Qiao, Hong.
其他作者:
Ma, Chao.
出版者:
Singapore :Springer Singapore : : 2022.,
面頁冊數:
xi, 178 p. :ill., digital ;24 cm.
內容註:
Introduction -- The Concept of "Attractive Region in Environment (ARIE)" and its Application in High-precision Tasks with Low-precision Systems -- The Compliance of Robotic Hands and Human-inspired Motion Model of Upper-limb with Fast Response and Learning Ability -- Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking -- Explicit Nonlinear Mapping for Manifold Learning with Neighborhood preserving polynomial embedding -- Biologically Inspired Visual Model with Memory and Association Mechanism -- Biologically Inspired Visual Model with Preliminary Cognition and Active Attention Adjustment -- Biologically Inspired Visual Cognition Model with Unsupervised Episodic and Semantic Feature Learning -- Conclusions and Future Research Directions.
Contained By:
Springer Nature eBook
標題:
Robot hands. -
電子資源:
https://doi.org/10.1007/978-981-16-3575-5
ISBN:
9789811635755
The "hand-eye-brain" system of intelligent robot = from interdisciplinary perspective of information science and neuroscience /
Qiao, Hong.
The "hand-eye-brain" system of intelligent robot
from interdisciplinary perspective of information science and neuroscience /[electronic resource] :by Hong Qiao, Chao Ma, Rui Li. - Singapore :Springer Singapore :2022. - xi, 178 p. :ill., digital ;24 cm. - Research on intelligent manufacturing,2523-3386. - Research on intelligent manufacturing..
Introduction -- The Concept of "Attractive Region in Environment (ARIE)" and its Application in High-precision Tasks with Low-precision Systems -- The Compliance of Robotic Hands and Human-inspired Motion Model of Upper-limb with Fast Response and Learning Ability -- Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking -- Explicit Nonlinear Mapping for Manifold Learning with Neighborhood preserving polynomial embedding -- Biologically Inspired Visual Model with Memory and Association Mechanism -- Biologically Inspired Visual Model with Preliminary Cognition and Active Attention Adjustment -- Biologically Inspired Visual Cognition Model with Unsupervised Episodic and Semantic Feature Learning -- Conclusions and Future Research Directions.
This book reports the new results of intelligent robot with hand-eye-brain, from the interdisciplinary perspective of information science and neuroscience. It collects novel research ideas on attractive region in environment (ARIE), intrinsic variable preserving manifold learning (IVPML) and biologically inspired visual congnition, which are theoretically important but challenging to develop the intelligent robot. Furthermore, the book offers new thoughts on the possible future development of human-inspired robotics, with vivid illustrations. The book is useful for researchers, R&D engineers and graduate students working on intelligent robots.
ISBN: 9789811635755
Standard No.: 10.1007/978-981-16-3575-5doiSubjects--Topical Terms:
901199
Robot hands.
LC Class. No.: TJ211.43 / .Q53 2022
Dewey Class. No.: 629.8933
The "hand-eye-brain" system of intelligent robot = from interdisciplinary perspective of information science and neuroscience /
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Introduction -- The Concept of "Attractive Region in Environment (ARIE)" and its Application in High-precision Tasks with Low-precision Systems -- The Compliance of Robotic Hands and Human-inspired Motion Model of Upper-limb with Fast Response and Learning Ability -- Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking -- Explicit Nonlinear Mapping for Manifold Learning with Neighborhood preserving polynomial embedding -- Biologically Inspired Visual Model with Memory and Association Mechanism -- Biologically Inspired Visual Model with Preliminary Cognition and Active Attention Adjustment -- Biologically Inspired Visual Cognition Model with Unsupervised Episodic and Semantic Feature Learning -- Conclusions and Future Research Directions.
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