Robotic tactile perception and understanding : a sparse coding method /: a sparse coding method. (2018)
- Record Type:
- Book
- Title:
- Robotic tactile perception and understanding : a sparse coding method /: a sparse coding method. (2018)
- Main Title:
- Robotic tactile perception and understanding : a sparse coding method
- Further Information:
- Note: Huaping Liu, Fuchun Sun.
- Authors:
- Liu, Huaping
Sun, Fuchun, 1964- - 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 andIntro; 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. … (more)
- Publisher Details:
- Singapore : Springer
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 629.8/933
Robot hands
Robots -- Programming
TECHNOLOGY & ENGINEERING -- Engineering (General)
Robot hands
Robots -- Programming
Electronic books
Electronic book - Languages:
- English
- ISBNs:
- 9789811061714
9811061718 - Related ISBNs:
- 9789811061707
981106170X - Notes:
- Note: Includes bibliographical references.
Note: Online resource; title from PDF title page (SpringerLink, viewed March 26, 2018). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.399943
- Ingest File:
- 02_433.xml