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ID 14213
file
creator
Terauchi, Mutsuhiro
subject
Impact control
impedance control
noncontact impedance
neural networks (NN)
robot manipulator
NDC
Mechanical engineering
abstract
Impedance control is one of the most effective methods forcontrolling the interaction between a manipulator and a task environment.In conventional impedance control methods, however, the manipulatorcannot be controlled until the end-effector contacts task environments. Anoncontact impedance control method has been proposed to resolve such aproblem. This method on only can regulate the end-point impedance, butalso the virtual impedance that works between the manipulator and theenvironment by using visual information. This paper proposes a learningmethod using neural networks to regulate the virtual impedance parametersaccording to a given task. The validity of the proposed method wasverified through computer simulations and experiments with a multijointrobotic manipulator.
journal title
IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics
volume
Volume 34
issue
Issue 5
start page
2112
end page
2118
date of issued
2004
publisher
IEEE
issn
1083-4419
language
eng
nii type
Journal Article
HU type
Journal Articles
DCMI type
text
format
application/pdf
text version
publisher
rights
Copyright (c) 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
relation is version of URL
http://dx.doi.org/10.1109/TSMCB.2004.829133
department
Graduate School of Engineering