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An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning

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dc.contributor.advisorBaşdoğan, Çağatay
dc.contributor.advisorid0000-0002-6382-7334
dc.contributor.authorNiaz, Pouya Pourakbarian
dc.contributor.instituteKoç University Graduate School of Sciences and Engineering
dc.contributor.programMechanical Engineering
dc.contributor.yokid125489
dc.date.accessioned2024-11-09T22:07:30Z
dc.date.issued2022
dc.descriptionxi, 54 leaves : illustrations, tables ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4912
dc.languageEnglish
dc.publisherKoç University
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectDrilling and boring
dc.subjectDrilling and boring machinery
dc.subjectRobotics
dc.subjectRobotics, Human factors
dc.subjectHuman-computer interaction
dc.thesis.degreeMaster's Degree
dc.thesis.grantorİstanbul
dc.titleAn adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning
dc.typeThesis
dspace.entity.typePublication
relation.isAdvisorOfThesis3296a078-6760-4af8-addd-62500c43ae7a
relation.isAdvisorOfThesis.latestForDiscovery3296a078-6760-4af8-addd-62500c43ae7a

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