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Article: Image measurement errors in visual servoing: Estimating the induced positioning error

TitleImage measurement errors in visual servoing: Estimating the induced positioning error
Authors
Issue Date2010
PublisherSpringer
Citation
Lecture Notes In Control And Information Sciences, 2010, v. 401, p. 151-167 How to Cite?
AbstractThe goal of a visual servo system is to position a robot end-effector by progressively adjusting its location so that some object features in the current image match the same features in a desired image previously recorded. However, this matching in the image domain cannot be ensured due to unavoidable presence of image measurement errors, and even when it is realized, there is no guarantee that the robot end-effector has reached the desired location since the available image measurements are corrupted. The aim of this chapter is to present a strategy for bounding the worst-case robot positioning error introduced by image measurement errors. In particular, two methods are described, which allow one to compute upper and lower bounds of this positioning error. Some examples illustrate the proposed methods with synthetic and real data. © 2010 Springer-Verlag London.
Persistent Identifierhttp://hdl.handle.net/10722/155563
ISBN
ISSN
2005 Impact Factor: 0.269
2015 SCImago Journal Rankings: 0.169
References

 

DC FieldValueLanguage
dc.contributor.authorChesi, Gen_US
dc.contributor.authorHung, YSen_US
dc.contributor.authorYung, HLen_US
dc.date.accessioned2012-08-08T08:34:07Z-
dc.date.available2012-08-08T08:34:07Z-
dc.date.issued2010en_US
dc.identifier.citationLecture Notes In Control And Information Sciences, 2010, v. 401, p. 151-167en_US
dc.identifier.isbn9781849960885-
dc.identifier.issn0170-8643en_US
dc.identifier.urihttp://hdl.handle.net/10722/155563-
dc.description.abstractThe goal of a visual servo system is to position a robot end-effector by progressively adjusting its location so that some object features in the current image match the same features in a desired image previously recorded. However, this matching in the image domain cannot be ensured due to unavoidable presence of image measurement errors, and even when it is realized, there is no guarantee that the robot end-effector has reached the desired location since the available image measurements are corrupted. The aim of this chapter is to present a strategy for bounding the worst-case robot positioning error introduced by image measurement errors. In particular, two methods are described, which allow one to compute upper and lower bounds of this positioning error. Some examples illustrate the proposed methods with synthetic and real data. © 2010 Springer-Verlag London.en_US
dc.languageengen_US
dc.publisherSpringer-
dc.relation.ispartofLecture Notes in Control and Information Sciencesen_US
dc.titleImage measurement errors in visual servoing: Estimating the induced positioning erroren_US
dc.typeArticleen_US
dc.identifier.emailChesi, G:chesi@eee.hku.hken_US
dc.identifier.emailHung, YS:yshung@eee.hku.hken_US
dc.identifier.authorityChesi, G=rp00100en_US
dc.identifier.authorityHung, YS=rp00220en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/978-1-84996-089-2_9en_US
dc.identifier.scopuseid_2-s2.0-77950211893en_US
dc.identifier.hkuros176727-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77950211893&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume401en_US
dc.identifier.spage151en_US
dc.identifier.epage167en_US
dc.publisher.placeBerlin, Germanyen_US
dc.identifier.scopusauthoridChesi, G=7006328614en_US
dc.identifier.scopusauthoridHung, YS=8091656200en_US
dc.identifier.scopusauthoridYung, HL=35172434900en_US

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