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Conference Paper: Perceptual docking for robotic control

TitlePerceptual docking for robotic control
Authors
KeywordsHaptics
Human-robot interfacing
3D tracking
Minimally invasive surgery
Robotic control
Perceptual docking
Perceptual feedback
Machine vision
Eye tracking
Deformation recovery
Autonomous robot
Issue Date2008
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, v. 5128 LNCS, p. 21-30 How to Cite?
AbstractIn current robotic surgery, dexterity is enhanced by microprocessor controlled mechanical wrists which allow motion scaling for reduced gross hand movements and improved performance of micro-scale tasks. The continuing evolution of the technology, including force feedback and virtual immobilization through real-time motion adaptation, will permit complex procedures such as beating heart surgery to be carried out under a static frame-of-reference. In pursuing more adaptive and intelligent robotic designs, the regulatory, ethical and legal barriers imposed on interventional surgical robots have given rise to the need of a tightly integrated control between the operator and the robot when autonomy is considered. This paper outlines the general concept of perceptual docking for robotic control and how it can be used for learning and knowledge acquisition in robotic assisted minimally invasive surgery such that operator specific motor and perceptual/cognitive behaviour is acquired through in situ sensing. A gaze contingent framework is presented in this paper as an example to illustrate how saccadic eye movements and ocular vergence can be used for attention selection, recovering 3D tissue deformation and motor channelling during minimally invasive surgical procedures. © 2008 Springer-Verlag Berlin Heidelberg.
Persistent Identifierhttp://hdl.handle.net/10722/199966
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorYang, Guangzhong-
dc.contributor.authorMylonas, George P.-
dc.contributor.authorKwok, Kawai-
dc.contributor.authorChung, Adrian-
dc.date.accessioned2014-07-26T23:10:58Z-
dc.date.available2014-07-26T23:10:58Z-
dc.date.issued2008-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, v. 5128 LNCS, p. 21-30-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/199966-
dc.description.abstractIn current robotic surgery, dexterity is enhanced by microprocessor controlled mechanical wrists which allow motion scaling for reduced gross hand movements and improved performance of micro-scale tasks. The continuing evolution of the technology, including force feedback and virtual immobilization through real-time motion adaptation, will permit complex procedures such as beating heart surgery to be carried out under a static frame-of-reference. In pursuing more adaptive and intelligent robotic designs, the regulatory, ethical and legal barriers imposed on interventional surgical robots have given rise to the need of a tightly integrated control between the operator and the robot when autonomy is considered. This paper outlines the general concept of perceptual docking for robotic control and how it can be used for learning and knowledge acquisition in robotic assisted minimally invasive surgery such that operator specific motor and perceptual/cognitive behaviour is acquired through in situ sensing. A gaze contingent framework is presented in this paper as an example to illustrate how saccadic eye movements and ocular vergence can be used for attention selection, recovering 3D tissue deformation and motor channelling during minimally invasive surgical procedures. © 2008 Springer-Verlag Berlin Heidelberg.-
dc.languageeng-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.subjectHaptics-
dc.subjectHuman-robot interfacing-
dc.subject3D tracking-
dc.subjectMinimally invasive surgery-
dc.subjectRobotic control-
dc.subjectPerceptual docking-
dc.subjectPerceptual feedback-
dc.subjectMachine vision-
dc.subjectEye tracking-
dc.subjectDeformation recovery-
dc.subjectAutonomous robot-
dc.titlePerceptual docking for robotic control-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-540-79982-5_3-
dc.identifier.scopuseid_2-s2.0-50249167229-
dc.identifier.volume5128 LNCS-
dc.identifier.spage21-
dc.identifier.epage30-
dc.identifier.eissn1611-3349-

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