ACTION-DRIVEN TACTILE OBJECT EXPLORATION FOR SHAPE RECONSTRUCTION VIA OPTICAL TACTILE SENSORS

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dc.contributor.authorMussin, Tleukhan
dc.date.accessioned2024-06-13T11:45:49Z
dc.date.available2024-06-13T11:45:49Z
dc.date.issued2024-04-19
dc.description.abstractWe introduce an action-driven tactile exploration system using novel optical tactile sensors integrated into the gripper of a robot arm. These sensors consist of multiple silicone layers, with one layer featuring alternating yellow and red patterns. When this layer deforms — typically by stretching and reducing in thickness—the colored patterns shift. These changes are captured by an onboard camera and analyzed using a Convolutional Neural Network (CNN) algorithm. The gripper for the sensor was specifically designed and 3D printed to ensure the sensors operate correctly. The colored part of the sensor was isolated from the external light. We tested the sensor’s effectiveness in edge detection and localization using four different geometric objects. We evaluated our system using a diverse collection of objects in both medium and large sizes.en_US
dc.identifier.citationMussin, T. (2024). Action-driven Tactile Object Exploration for Shape Reconstruction via Optical Tactile Sensors. Nazarbayev University School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7863
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectTactile Sensorsen_US
dc.subjectType of access: Restricteden_US
dc.titleACTION-DRIVEN TACTILE OBJECT EXPLORATION FOR SHAPE RECONSTRUCTION VIA OPTICAL TACTILE SENSORSen_US
dc.typeBachelor's thesisen_US
workflow.import.sourcescience

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