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Conference Paper: Designing image trajectories in the presence of uncertain data for robust visual servoing path-planning

TitleDesigning image trajectories in the presence of uncertain data for robust visual servoing path-planning
Authors
KeywordsEye-in-hand
Path-planning
Robustness
Uncertainty
Visual servoing
Issue Date2009
Citation
IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 12 -17 May 2009. In I E E E International Conference on Robotics and Automation Proceedings, 2009, p. 1492-1497 How to Cite?
AbstractPath-planning allows one to steer a camera to a desired location while taking into account the presence of constraints such as visibility, workspace, and joint limits. Unfortunately, the planned path can be significantly different from the real path due to the presence of uncertainty on the available data, with the consequence that some constraints may be not fulfilled by the real path even if they are satisfied by the planned path. In this paper we address the problem of performing robust path-planning, i.e. computing a path that satisfies the required constraints not only for the nominal model as in traditional path-planning but rather for a family of admissible models. Specifically, we consider an uncertain model where the point correspondences between the initial and desired views and the camera intrinsic parameters are affected by unknown random uncertainties with known bounds. The difficulty we have to face is that traditional path-planning schemes applied to different models lead to different paths rather than to a common and robust path. To solve this problem we propose a technique based on polynomial optimization where the required constraints are imposed on a number of trajectories corresponding to admissible camera poses and parameterized by a common design variable. The planned image trajectory is then followed by using an IBVS controller. Simulations carried out with all typical uncertainties that characterize a real experiment illustrate the proposed strategy and provide promising results. © 2009 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/62098
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChesi, Gen_HK
dc.date.accessioned2010-07-13T03:53:51Z-
dc.date.available2010-07-13T03:53:51Z-
dc.date.issued2009en_HK
dc.identifier.citationIEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 12 -17 May 2009. In I E E E International Conference on Robotics and Automation Proceedings, 2009, p. 1492-1497en_HK
dc.identifier.issn1050-4729en_HK
dc.identifier.urihttp://hdl.handle.net/10722/62098-
dc.description.abstractPath-planning allows one to steer a camera to a desired location while taking into account the presence of constraints such as visibility, workspace, and joint limits. Unfortunately, the planned path can be significantly different from the real path due to the presence of uncertainty on the available data, with the consequence that some constraints may be not fulfilled by the real path even if they are satisfied by the planned path. In this paper we address the problem of performing robust path-planning, i.e. computing a path that satisfies the required constraints not only for the nominal model as in traditional path-planning but rather for a family of admissible models. Specifically, we consider an uncertain model where the point correspondences between the initial and desired views and the camera intrinsic parameters are affected by unknown random uncertainties with known bounds. The difficulty we have to face is that traditional path-planning schemes applied to different models lead to different paths rather than to a common and robust path. To solve this problem we propose a technique based on polynomial optimization where the required constraints are imposed on a number of trajectories corresponding to admissible camera poses and parameterized by a common design variable. The planned image trajectory is then followed by using an IBVS controller. Simulations carried out with all typical uncertainties that characterize a real experiment illustrate the proposed strategy and provide promising results. © 2009 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofI E E E International Conference on Robotics and Automation Proceedingsen_HK
dc.rightsI E E E International Conference on Robotics and Automation Proceedings. Copyright © I E E E, Computer Society.-
dc.rights©2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectEye-in-handen_HK
dc.subjectPath-planningen_HK
dc.subjectRobustnessen_HK
dc.subjectUncertaintyen_HK
dc.subjectVisual servoingen_HK
dc.titleDesigning image trajectories in the presence of uncertain data for robust visual servoing path-planningen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChesi, G:chesi@eee.hku.hken_HK
dc.identifier.authorityChesi, G=rp00100en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ROBOT.2009.5152226en_HK
dc.identifier.scopuseid_2-s2.0-70350357043en_HK
dc.identifier.hkuros156202en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70350357043&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1492en_HK
dc.identifier.epage1497en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChesi, G=7006328614en_HK
dc.identifier.citeulike9667016-

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