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dc.contributor.advisorÇavuşoğlu, Cenk
dc.contributor.authorTuna, Eser Erdem
dc.date.accessioned2016-01-08T18:15:52Z
dc.date.available2016-01-08T18:15:52Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/11693/15269
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2011.en_US
dc.descriptionIncludes bibliographical references leaves 90-93.en_US
dc.description.abstractRobotic assisted beating heart surgery aims to allow surgeons to operate on a beating heart without stabilizers as if the heart is stationary. The robot actively cancels heart motion by closely following a point of interest (POI) on the heart surface—a process called Active Relative Motion Canceling (ARMC). Due to the high bandwidth of the POI motion, it is necessary to supply the controller with an estimate of the immediate future of the POI motion over a prediction horizon in order to achieve sufficient tracking accuracy. In this thesis two prediction algorithms, using an adaptive filter to generate future position estimates, are studied. In addition, the variation in heart rate on tracking performance is studied and the prediction algorithms are evaluated using a 3 degrees of freedom test-bed with prerecorded heart motion data. Besides this, a probabilistic robotics approach is followed to model and characterize noise of the sensor system that collects heart motion data used in this study. The generated model is employed to filter and clean the noisy measurements collected from the sensor system. Then, the filtered sensor data is used to localize POI on the heart surface accurately. Finally, estimates obtained from the adaptive prediction algorithms are integrated to the generated measurement model with the aim of improving the performance of the presented approach.en_US
dc.description.statementofresponsibilityTuna, Eser Erdemen_US
dc.format.extentxiv, 99 leaves, illustrationsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectActive relative motion cancelingen_US
dc.subjectsignal estimationen_US
dc.subjectmedical roboticsen_US
dc.subjectsurgical roboticsen_US
dc.subjectprobabilistic roboticsen_US
dc.subject.lccWG169 .T85 2011en_US
dc.subject.lcshHeart--Surgery--Data processing.en_US
dc.subject.lcshRobotics in medicine.en_US
dc.subject.lcshProbabilities.en_US
dc.subject.lcshComputer-assisted surgery.en_US
dc.subject.lcshSignal processing--Digital techniques.en_US
dc.subject.lcshMotion perception (Vision)en_US
dc.subject.lcshEstimation theory.en_US
dc.titleHeart motion prediction based on adaptive estimation aşgorithms fo robotic-assisted beating heart surgeryen_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


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