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abstract: 'The control of light-weight compliant robot arms is cumbersome due to the fact that their Coriolis forces are large, and the forces exerted by the relatively weak actuators may change in time due to external (e.g., temperature) influences. We describe and analyse the behaviour of a light-weight robot arm, the SoftArm robot. It is found that the hysteretic force-position relationship of the arm can be explained from its structure. This knowledge is used in the construction of a neural-network based controller. Experiments show that the network is able to accurately control the robot arm after a training session of only a few minutes.'
altloc:
- http://www.robotic.dlr.de/Smagt/papers/SmaGroSch96.ps.gz
chapter: ~
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creators_name:
- family: Smagt
given: P. van der
honourific: ''
lineage: ''
- family: Groen
given: F.
honourific: ''
lineage: ''
- family: Schulten
given: K.
honourific: ''
lineage: ''
date: 1996
date_type: published
datestamp: 1998-07-03
department: ~
dir: disk0/00/00/04/92
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eprint_status: archive
eprintid: 492
fileinfo: /style/images/fileicons/application_postscript.png;/492/2/SmaGroSch96.ps
full_text_status: public
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keywords: 'robot arm dynamics, light-weight robot, feed-forward network, learning, rubbertuator, SoftArm, analysis'
lastmod: 2011-03-11 08:54:00
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: 5
pagerange: 433-440
pubdom: FALSE
publication: Biological Cybernetics
publisher: ~
refereed: TRUE
referencetext: ~
relation_type: []
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reportno: ~
rev_number: 10
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source: ~
status_changed: 2007-09-12 16:28:58
subjects:
- comp-sci-neural-nets
- comp-sci-robot
succeeds: ~
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thesistype: ~
title: Analysis and control of a rubbertuator arm
type: journalp
userid: 462
volume: 75