From Robot to Human Grasping Simulation (Hardcover, 2014 ed.)

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand's functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand's function for grasping and manipulation of everyday life objects. This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Cognitive Systems Monographs, 19
Release date:	October 2013
First published:	2014
Authors:	Beatriz Leon • Antonio Morales • Joaquin Sancho-Bru
Dimensions:	235 x 155 x 20mm (L x W x T)
Format:	Hardcover
Pages:	261
Edition:	2014 ed.
ISBN-13:	978-3-319-01832-4
Categories:	Books > Medicine > Nursing & ancillary services > Biomedical engineering > General Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
LSN:	3-319-01832-9
Barcode:	9783319018324

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