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The“Hand-eye-brain”SystemofIntelligentRobot

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浙江嘉兴

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作者乔红,马超,李瑞

出版社华中科技大学

ISBN9787568075596

出版时间2021-11

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开本其他

定价168元

货号31296740

上书时间2024-10-13

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商品描述: 作者简介
乔红，中国科学院自动化所研究员，博士生导师，国家杰出青年基金获得者；获2014年国家自然科学奖二等奖（第一完成人），2012年北京市科学技术一等奖（基础研究类，排名第一），2015年北京市科学技术二等奖（技术发明类，排名第一）;2013年当选全球IEEERAS（机器人与自动化学会）管理委员会委员。乔红研究员于2004年引进回国并创建中国科学院自动化所“机器人理论与应用”团队（规模50余人），目前担任中国科学院自动化研究所“类脑智能研究中心”副主任（负责类脑神经机器人方向，是中心三个方向之一），中国科学院大学计算机与控制学院“控制理论与控制工程”教研室主任，中国科学院自动化研究所-中国科学技术大学联合实验室副主任，中国科学院“脑科学与智能技术卓越中心”核心骨干（机器人方向唯一核心骨干），九三学社中央科技委委员。

目录
Part I  Introduction
  1  Background
    References
  2  Motivations
    References
  3  Structure of the Book
Part II  The Hand of Robots-Intelligent Manipulation Theory and Application of Robots
  4  The Development and Challenges of Robot Manipulation
     References
  5  The Concept of \"Attractive Region in Environment (ARIE)\" and Its Application in High-Precision Tasks with Low-Precision Systems
    5.1  General Concept of \"Attractive Region in Environment\"
    5.2  General Formulation of \"Attractive Region in Environment\"
    5.3  Extension of Attractive Region in High Dimensional Space
    5.4  Applications of \"Attractive Region in Environment\" in Industrial Manufacturing
    5.5  Conclusions
    References
  6  The Compliance of Robotic Hands and Human-Inspired Motion Model of Upper-Limb with Fast Response and Learning Ability
    6.1  The Combination of Compliance and Robotic Hands from Functionality to Mechanism
    6.2  Forward Dynamics of the Upper Limb
    6.3  Movement Control Method Based on the Patterns
    6.4  Experiment Results
    6.5  Conclusions
    References
Part III  The Eye of Robots-Intelligent Perception Theory and Application of Robots
  7  The Development and Challenges of Robot Perception References
  8  Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking
    8.1  Intrinsic Variable Preserving Manifold Learning (IVPML)
    8.2  Visual-Head-Tracking Algorithm with Complicated Backgrounds Using IVPML
    8.3  Experiment Results
    8.4  Conclusions
    References
  9  Explicit Nonlinear Mapping for Manifold Learning
    with Neighborhood Preserving Polynomial Embedding
    9.1  Explicit Nonlinear Manifold Learning Model
    9.2  Neighborhood Preserving Polynomial Embedding (NPPE) Algorithm
    9.3  Experiment Results
    9.4  Conclusions
    References
Part IV  The Brain of Robots-Intelligent Cognition Theory and Application of Robots
  10  The Development and Challenges of Robot Cognition
  11  Biologically Inspired Visual Model with Memory and Association Mechanism
    11.1  Biological Evidences for Memory and Association Mechanism
    11.2  Visual Model with Memory and Association Mechanism
    11.2.1  Familiarity Discrimination
    11.3  Experiment Results
    11.4  Conclusions
    References
  12  Biologically Inspired Visual Model with Preliminary Cognition and Active Attention Adjustment
    12.1  Biological Evidences for Preliminary Cognition and Active Attention Adjustment
    12.2  Visual Model with Preliminary Cognition and Active Attention Adjustment
    12.3  Experiment Results
    12.4  Conclusions
    References
  13  Biologically Inspired Visual Cognition Model with Unsupervised Episodic and Semantic Feature Learning
    13.1  Biological Evidences for Human Visual Cognition
    13.2  Visual Model with Unsupervised Episodic and Semantic Feature Learning
    13.3  Experiment Results
    13.4  Conclusions
    References
Part V  Conclusions and Future Research Directions
  14  Conclusions

内容摘要
Thisbookreportsthenewresultsofintelligentrobotwithhand-eye-brain,fromtheinterdisciplinaryperspectiveofinformationscienceandneuroscience.Itcollectsnovelresearchideasonattractiveregioninenvironment(ARIE),intrinsicvariablepreservingmanifoldlearning(IVPML)andbiologicallyinspiredvisualcongnition,whicharetheoreticallyimportantbutchallengingtodeveloptheintelligentrobot.Furthermore,thebookoffersnewthoughtsonthepossiblefuturedevelopmentofhuman-inspiredrobotics,withvividillustrations.Thebookisusefulforresearchers,R&Dengineersandgraduatestudentsworkingonintelligentrobots.

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The“Hand-eye-brain”SystemofIntelligentRobot

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