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The Resource Robotic tactile perception and understanding : a sparse coding method, Huaping Liu, Fuchun Sun

Robotic tactile perception and understanding : a sparse coding method, Huaping Liu, Fuchun Sun

Label
Robotic tactile perception and understanding : a sparse coding method
Title
Robotic tactile perception and understanding
Title remainder
a sparse coding method
Statement of responsibility
Huaping Liu, Fuchun Sun
Creator
Contributor
Author
Subject
Language
eng
Summary
This book introduces the challenges of robotic tactile perception and task understanding, and describes an advanced approach based on machine learning and sparse coding techniques. Further, a set of structured sparse coding models is developed to address the issues of dynamic tactile sensing. The book then proves that the proposed framework is effective in solving the problems of multi-finger tactile object recognition, multi-label tactile adjective recognition and multi-category material analysis, which are all challenging practical problems in the fields of robotics and automation. The proposed sparse coding model can be used to tackle the challenging visual-tactile fusion recognition problem, and the book develops a series of efficient optimization algorithms to implement the model. It is suitable as a reference book for graduate students with a basic knowledge of machine learning as well as professional researchers interested in robotic tactile perception and understanding, and machine learning
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Liu, Huaping
Dewey number
629.8/933
Index
no index present
LC call number
TJ211.43
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1964-
http://library.link/vocab/relatedWorkOrContributorName
Sun, Fuchun
http://library.link/vocab/subjectName
  • Robot hands
  • Robots
  • Computer Science
  • Artificial Intelligence (incl. Robotics)
  • Pattern Recognition
  • Image Processing and Computer Vision
Label
Robotic tactile perception and understanding : a sparse coding method, Huaping Liu, Fuchun Sun
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro; Foreword; Preface; Acknowledgements; Contents; Acronyms; Mathematical Notation; Part I Background; 1 Introduction; 1.1 Robotic Manipulation and Grasp; 1.2 Robotic Tactile Perception; 1.3 Tactile Exploratory Procedure; 1.4 Tactile Perception for Shape; 1.5 Tactile Perception for Texture; 1.6 Tactile Perception for Deformable Objects; 1.7 Visual-Tactile Fusion for Object Recognition; 1.8 Public Datasets; 1.8.1 Tactile Dataset; 1.8.2 Visual-Tactile Fusion Datasets; 1.9 Summary; References; 2 Representation of Tactile and Visual Modalities; 2.1 Tactile Modality Representation
  • 2.1.1 Tactile Sequence2.1.2 Dynamic Time Warping Distance; 2.1.3 Global Alignment Kernel; 2.2 Visual Modality Representation; 2.3 Summary; References; Part II Tactile Perception; 3 Tactile Object Recognition Using Joint Sparse Coding; 3.1 Introduction; 3.2 Kernel Sparse Coding; 3.3 Joint Kernel Sparse Coding; 3.4 Experimental Results; 3.4.1 Data Collection; 3.4.2 Result Analysis; 3.4.3 Results for the Public Dataset; 3.5 Summary; References; 4 Tactile Object Recognition Using Supervised Dictionary Learning; 4.1 Introduction; 4.2 Tactile Dictionary Learning; 4.3 Extreme Learning Machines
  • 4.4 Extreme Kernel Sparse Learning4.5 Reduced Extreme Kernel Sparse Learning; 4.6 Optimization Algorithm; 4.6.1 Calculating the Sparse Coding Vectors; 4.6.2 Calculating the Dictionary Atoms; 4.6.3 Calculating the ELM Coefficients; 4.7 Algorithm Analysis; 4.8 Experimental Results; 4.8.1 Data Description and Experimental Setting; 4.8.2 Parameter Selection; 4.8.3 Accuracy Performance Comparison; 4.8.4 Comparison of Reduced Strategies; 4.9 Summary; References; 5 Tactile Adjective Understanding Using Structured Output-Associated Dictionary Learning; 5.1 Introduction; 5.2 Problem Formulation
  • 5.3 Optimization Algorithm5.3.1 Calculating the Sparse Coding Vectors; 5.3.2 Calculating the Dictionary Atoms; 5.3.3 Calculating the Classifier Parameters; 5.3.4 Algorithm Summarization; 5.4 Classifier Design; 5.5 Experimental Results; 5.5.1 Data Description and Experimental Setting; 5.5.2 Performance Comparison; 5.5.3 Parameter Sensitivity Analysis; 5.6 Summary; References; 6 Tactile Material Identification Using Semantics-Regularized Dictionary Learning; 6.1 Introduction; 6.2 Linearized Tactile Feature Representation; 6.3 Motivation and Problem Formulation; 6.4 Proposed Model
  • 6.5 Optimization Algorithm6.5.1 Calculating the Sparse Coding Vectors; 6.5.2 Calculating the Dictionary Atoms; 6.5.3 Algorithm Summarization; 6.6 Classifier Design; 6.7 Experimental Results; 6.7.1 Experimental Setting; 6.7.2 Performance Comparison; 6.8 Summary; References; Part III Visual-Tactile Fusion Perception; 7 Visual-Tactile Fusion Object Recognition Using Joint Sparse Coding; 7.1 Introduction; 7.2 Problem Formulation; 7.3 Kernel Sparse Coding for Visual-Tactile Fusion; 7.3.1 Kernel Sparse Coding; 7.3.2 Joint Kernel Group Sparse Coding; 7.4 Experimental Results; 7.4.1 Data Collection
Control code
SPR1029352614
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9789811061707
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-981-10-6171-4
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1029352614
  • (OCoLC)1029352614
Label
Robotic tactile perception and understanding : a sparse coding method, Huaping Liu, Fuchun Sun
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro; Foreword; Preface; Acknowledgements; Contents; Acronyms; Mathematical Notation; Part I Background; 1 Introduction; 1.1 Robotic Manipulation and Grasp; 1.2 Robotic Tactile Perception; 1.3 Tactile Exploratory Procedure; 1.4 Tactile Perception for Shape; 1.5 Tactile Perception for Texture; 1.6 Tactile Perception for Deformable Objects; 1.7 Visual-Tactile Fusion for Object Recognition; 1.8 Public Datasets; 1.8.1 Tactile Dataset; 1.8.2 Visual-Tactile Fusion Datasets; 1.9 Summary; References; 2 Representation of Tactile and Visual Modalities; 2.1 Tactile Modality Representation
  • 2.1.1 Tactile Sequence2.1.2 Dynamic Time Warping Distance; 2.1.3 Global Alignment Kernel; 2.2 Visual Modality Representation; 2.3 Summary; References; Part II Tactile Perception; 3 Tactile Object Recognition Using Joint Sparse Coding; 3.1 Introduction; 3.2 Kernel Sparse Coding; 3.3 Joint Kernel Sparse Coding; 3.4 Experimental Results; 3.4.1 Data Collection; 3.4.2 Result Analysis; 3.4.3 Results for the Public Dataset; 3.5 Summary; References; 4 Tactile Object Recognition Using Supervised Dictionary Learning; 4.1 Introduction; 4.2 Tactile Dictionary Learning; 4.3 Extreme Learning Machines
  • 4.4 Extreme Kernel Sparse Learning4.5 Reduced Extreme Kernel Sparse Learning; 4.6 Optimization Algorithm; 4.6.1 Calculating the Sparse Coding Vectors; 4.6.2 Calculating the Dictionary Atoms; 4.6.3 Calculating the ELM Coefficients; 4.7 Algorithm Analysis; 4.8 Experimental Results; 4.8.1 Data Description and Experimental Setting; 4.8.2 Parameter Selection; 4.8.3 Accuracy Performance Comparison; 4.8.4 Comparison of Reduced Strategies; 4.9 Summary; References; 5 Tactile Adjective Understanding Using Structured Output-Associated Dictionary Learning; 5.1 Introduction; 5.2 Problem Formulation
  • 5.3 Optimization Algorithm5.3.1 Calculating the Sparse Coding Vectors; 5.3.2 Calculating the Dictionary Atoms; 5.3.3 Calculating the Classifier Parameters; 5.3.4 Algorithm Summarization; 5.4 Classifier Design; 5.5 Experimental Results; 5.5.1 Data Description and Experimental Setting; 5.5.2 Performance Comparison; 5.5.3 Parameter Sensitivity Analysis; 5.6 Summary; References; 6 Tactile Material Identification Using Semantics-Regularized Dictionary Learning; 6.1 Introduction; 6.2 Linearized Tactile Feature Representation; 6.3 Motivation and Problem Formulation; 6.4 Proposed Model
  • 6.5 Optimization Algorithm6.5.1 Calculating the Sparse Coding Vectors; 6.5.2 Calculating the Dictionary Atoms; 6.5.3 Algorithm Summarization; 6.6 Classifier Design; 6.7 Experimental Results; 6.7.1 Experimental Setting; 6.7.2 Performance Comparison; 6.8 Summary; References; Part III Visual-Tactile Fusion Perception; 7 Visual-Tactile Fusion Object Recognition Using Joint Sparse Coding; 7.1 Introduction; 7.2 Problem Formulation; 7.3 Kernel Sparse Coding for Visual-Tactile Fusion; 7.3.1 Kernel Sparse Coding; 7.3.2 Joint Kernel Group Sparse Coding; 7.4 Experimental Results; 7.4.1 Data Collection
Control code
SPR1029352614
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9789811061707
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-981-10-6171-4
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1029352614
  • (OCoLC)1029352614

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