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Human and Robot Hands

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Cover of 'Human and Robot Hands'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Dexterous Manipulation: From High-Level Representation to Low-Level Coordination of Digit Forces and Positions
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    Chapter 3 Digit Position and Force Synergies During Unconstrained Grasping
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    Chapter 4 The Motor Control of Hand Movements in the Human Brain: Toward the Definition of a Cortical Representation of Postural Synergies
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    Chapter 5 Synergy Control in Subcortical Circuitry: Insights from Neurophysiology
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    Chapter 6 Neuronal “Op-amps” Implement Adaptive Control in Biology and Robotics
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    Chapter 7 Sensorymotor Synergies: Fusion of Cutaneous Touch and Proprioception in the Perceived Hand Kinematics
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    Chapter 8 From Soft to Adaptive Synergies: The Pisa/IIT SoftHand
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    Chapter 9 A Learn by Demonstration Approach for Closed-Loop, Robust, Anthropomorphic Grasp Planning
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    Chapter 10 Teleimpedance Control: Overview and Application
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    Chapter 11 Incremental Learning of Muscle Synergies: From Calibration to Interaction
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    Chapter 12 How to Map Human Hand Synergies onto Robotic Hands Using the SynGrasp Matlab Toolbox
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    Chapter 13 Quasi-Static Analysis of Synergistically Underactuated Robotic Hands in Grasping and Manipulation Tasks
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    Chapter 14 A Simple Model of the Hand for the Analysis of Object Exploration
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    Chapter 15 Synergy-Based Optimal Sensing Techniques for Hand Pose Reconstruction
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48 Mendeley
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Title
Human and Robot Hands
Published by
Springer International Publishing, February 2016
DOI 10.1007/978-3-319-26706-7
ISBNs
978-3-31-926705-0, 978-3-31-926706-7
Editors

Bianchi, Matteo, Moscatelli, Alessandro

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 23%
Student > Master 10 21%
Researcher 10 21%
Student > Doctoral Student 3 6%
Professor 3 6%
Other 7 15%
Unknown 4 8%
Readers by discipline Count As %
Engineering 27 56%
Computer Science 5 10%
Agricultural and Biological Sciences 4 8%
Neuroscience 2 4%
Mathematics 1 2%
Other 5 10%
Unknown 4 8%