Slip-Aware Robotic Handling: Tactile Object Characterization for Safe Manipulation

dc.contributor.advisorChen, Xu
dc.contributor.authorKaur, Navneet
dc.date.accessioned2024-10-16T03:16:14Z
dc.date.available2024-10-16T03:16:14Z
dc.date.issued2024-10-16
dc.date.submitted2024
dc.descriptionThesis (Master's)--University of Washington, 2024
dc.description.abstractSlip is a significant challenge in manipulative tasks involving object gripping. Most research has focused on hard or deformable objects rather than simultaneously addressing both. This study develops and implements a robust slip detection mechanism that effectively identifies slips across various types of objects. The study also introduces a method for classifying objects based on tactile sensor images to determine whether they are hard or deformable. A gripper control method that utilizes this classification to enhance the handling of different object types is proposed.
dc.embargo.termsOpen Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherKaur_washington_0250O_27532.pdf
dc.identifier.urihttps://hdl.handle.net/1773/52569
dc.language.isoen_US
dc.rightsnone
dc.subjectFeedback Control
dc.subjectFeedforward Control
dc.subjectGripper Control
dc.subjectMachine Learning
dc.subjectObject Characterization
dc.subjectTactile Sensors
dc.subjectRobotics
dc.subjectMechanical engineering
dc.subjectComputer science
dc.subject.otherMechanical engineering
dc.titleSlip-Aware Robotic Handling: Tactile Object Characterization for Safe Manipulation
dc.typeThesis

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