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Human and Robot Hands: Sensorimotor Synergies to Bridge the Gap Between Neuroscience and Robotics 1st ed. 2016 [Kõva köide]

  • Formaat: Hardback, 283 pages, kõrgus x laius: 235x155 mm, kaal: 5679 g, 31 Illustrations, color; 66 Illustrations, black and white; XI, 283 p. 97 illus., 31 illus. in color., 1 Hardback
  • Sari: Springer Series on Touch and Haptic Systems
  • Ilmumisaeg: 03-Mar-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319267051
  • ISBN-13: 9783319267050
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  • Formaat: Hardback, 283 pages, kõrgus x laius: 235x155 mm, kaal: 5679 g, 31 Illustrations, color; 66 Illustrations, black and white; XI, 283 p. 97 illus., 31 illus. in color., 1 Hardback
  • Sari: Springer Series on Touch and Haptic Systems
  • Ilmumisaeg: 03-Mar-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319267051
  • ISBN-13: 9783319267050
This book looks at the common problems both human and robotic hands encounter when controlling the large number of joints, actuators and sensors required to efficiently perform motor tasks such as object exploration, manipulation and grasping. The authors adopt an integrated approach to explore the control of the hand based on sensorimotor synergies that can be applied in both neuroscience and robotics.  Hand synergies are based on goal-directed, combined muscle and kinematic activation leading to a reduction of the dimensionality of the motor and sensory space, presenting a highly effective solution for the fast and simplified design of artificial systems.









Presented in two parts, the first part, Neuroscience, provides the theoretical and experimental foundations to describe the synergistic organization of the human hand. The second part, Robotics, Models and Sensing Tools, exploits the framework of hand synergies to better control and design robotic hands and haptic/sensing systems/tools, using a reduced number of control inputs/sensors, with the goal of pushing their effectiveness close to the natural one.









Human and Robot Hands provides a valuable reference for students, researchers and designers who are interested in the study and design of the artificial hand.

Arvustused

Neuroscience deals with the controlling of senses in humans and their function in the day-to-day work of the human body. In parallel, the robotics field is developing artificial senses or their capabilities in robots. This book discusses human and robot hands. This book is an interesting read for researchers, doctoral students, and professionals working in the area of neuroscience and robotics. (Lalit Saxena, Computing Reviews, March, 2017)

1 Introduction
1(8)
Matteo Bianchi
Alessandro Moscatelli
Part I Neuroscience
2 Dexterous Manipulation: From High-Level Representation to Low-Level Coordination of Digit Forces and Positions
9(20)
Qiushi Fu
Marco Santello
3 Digit Position and Force Synergies During Unconstrained Grasping
29(12)
Abdeldjallil Naceri
Marco Santello
Alessandro Moscatelli
Marc O. Ernst
4 The Motor Control of Hand Movements in the Human Brain: Toward the Definition of a Cortical Representation of Postural Synergies
41(20)
Andrea Leo
Giacomo Handjaras
Hamal Marino
Matteo Bianchi
Pietro Pietrini
Emiliano Ricciardi
5 Synergy Control in Subcortical Circuitry: Insights from Neurophysiology
61(8)
Henrik Jorntell
6 Neuronal "Op-amps" Implement Adaptive Control in Biology and Robotics
69(18)
Martin Nilsson
7 Sensorymotor Synergies: Fusion of Cutaneous Touch and Proprioception in the Perceived Hand Kinematics
87(14)
Alessandro Moscatelli
Matteo Bianchi
Alessandro Serio
Antonio Bicchi
Marc O. Ernst
Part II Robotics, Models and Sensing Tools
8 From Soft to Adaptive Synergies: The Pisa/IIT SoftHand
101(26)
Manuel G. Catalano
Giorgio Grioli
Edoardo Farnioli
Alessandro Serio
Manuel Bonilla
Manolo Garabini
Cristina Piazza
Marco Gabiccini
Antonio Bicchi
9 A Learn by Demonstration Approach for Closed-Loop, Robust, Anthropomorphic Grasp Planning
127(24)
Minas V. Liarokapis
Charalampos P. Bechlioulis
George I. Boutselis
Kostas J. Kyriakopoulos
10 Teleimpedance Control: Overview and Application
151(20)
Arash Ajoudani
Sasha B. Godfrey
Nikos Tsagarakis
Antonio Bicchi
11 Incremental Learning of Muscle Synergies: From Calibration to Interaction
171(24)
Claudio Castellini
12 How to Map Human Hand Synergies onto Robotic Hands Using the SynGrasp Matlab Toolbox
195(16)
Gionata Salvietti
Guido Gioioso
Monica Malvezzi
Domenico Prattichizzo
13 Quasi-Static Analysis of Synergistically Underactuated Robotic Hands in Grasping and Manipulation Tasks
211(24)
Edoardo Farnioli
Marco Gabiccini
Antonio Bicchi
14 A Simple Model of the Hand for the Analysis of Object Exploration
235(24)
Vonne van Polanen
Wouter M. Bergmann Tiest
Astrid M.L. Kappers
15 Synergy-Based Optimal Sensing Techniques for Hand Pose Reconstruction
259
Matteo Bianchi
Paolo Salaris
Antonio Bicchi