---
abstract: 'In this chapter we introduce a method for model-free monocular visual guidance of a robot arm. The robot arm, with a single camera in its end effector, should be positioned above a stationary target. It is shown that a trajectory can be planned in visual space by using components of the optic flow, and this trajector can be translated to joint torques by a self-learning neural network. No model of the robot, camera, or environment is used. The method reaches a high grasping accuracy after only a few trials.'
altloc:
- http://www.robotic.dlr.de/Smagt/papers/SmaGro97.ps.gz
chapter: 3
commentary: ~
commref: ~
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contact_email: ~
creators_id: []
creators_name:
- family: Smagt
given: P. van der
honourific: ''
lineage: ''
- family: Groen
given: F.
honourific: ''
lineage: ''
date: 1997
date_type: published
datestamp: 1998-07-03
department: ~
dir: disk0/00/00/04/93
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editors_id: []
editors_name:
- family: Omidvar
given: O. and Smagt
honourific: ''
lineage: ''
eprint_status: archive
eprintid: 493
fileinfo: /style/images/fileicons/application_postscript.png;/493/2/SmaGro97.ps
full_text_status: public
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isbn: ~
ispublished: pub
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item_issues_comment: []
item_issues_count: 0
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keywords: ~
lastmod: 2011-03-11 08:54:00
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metadata_visibility: show
note: ~
number: ~
pagerange: 37-73
pubdom: FALSE
publication: Neural Systems for Robotics
publisher: 'Academic Press, Boston, Massachusetts'
refereed: FALSE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 10
series: ~
source: ~
status_changed: 2007-09-12 16:29:01
subjects:
- bio-ani-cog
- comp-sci-mach-vis
- comp-sci-neural-nets
- comp-sci-robot
succeeds: ~
suggestions: ~
sword_depositor: ~
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thesistype: ~
title: Visual feedback in motion
type: bookchapter
userid: 462
volume: ~