{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120333"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120333","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Autonomous object model acquisition with parallel jaw gripper","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","abstract_has_math":false,"creators":["Colthurst, Victoria Ruth"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Kim, Joohyung"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Robotics","Robot","Robots","3d","Three","Dimensions","Autonomous","Object","Model","Acquisition","Gripper","Grasp","Grasping","Geometric","Grasps","Geometry-based","Geometry","Registration","Point","Cloud","Clouds","Reconstruction","Cluttered","Rotation","Papras","Plug","Robotic","Depth","Scan","Scans"],"languages":["en","eng"],"rights":["Copyright 2023 Victoria Colthurst"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120333","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kim, Joohyung"]},{"key":"dc:creator","label":"Author","values":["Colthurst, Victoria Ruth"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-01-23"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Robotics","Robot","Robots","3d","Three","Dimensions","Autonomous","Object","Model","Acquisition","Gripper","Grasp","Grasping","Geometric","Grasps","Geometry-based","Geometry","Registration","Point","Cloud","Clouds","Reconstruction","Cluttered","Rotation","Papras","Plug","Robotic","Depth","Scan","Scans"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Victoria Colthurst"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120333"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","The student, Victoria Colthurst, accepted the attached license on 2023-01-18 at 13:15.","The student, Victoria Colthurst, submitted this Thesis for approval on 2023-01-18 at 13:44.","This Thesis was approved for publication on 2023-01-23 at 14:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18824 on 2023-09-01 at 17:12:31","Granting robots the ability to identify and interact with any object in a cluttered, real-world environment requires solutions that tackle partial visibility and object novelty. Humans overcome this challenge with experience, which we emulate by developing a method to build a database of known 3D object models over time. We present an autonomous object registration pipeline deployed on a self-contained camera and robotic arm hardware system that produces 3D object point clouds. Experimentation evaluates the quantitative and qualitative aspects of the produced point clouds, and we show that our methods produce representations comparable with state-of-the-art methods. It is our hope that the solution presented in this thesis will aid in perception-based tasks that require identifying and interacting with objects in an unstructured environment."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Autonomous object model acquisition with parallel jaw gripper"]}]}],"canonical_facts":{"dc:contributor":["Kim, Joohyung"],"dc:creator":["Colthurst, Victoria Ruth"],"dc:date":["2023-05","2023-01-23"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","The student, Victoria Colthurst, accepted the attached license on 2023-01-18 at 13:15.","The student, Victoria Colthurst, submitted this Thesis for approval on 2023-01-18 at 13:44.","This Thesis was approved for publication on 2023-01-23 at 14:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18824 on 2023-09-01 at 17:12:31","Granting robots the ability to identify and interact with any object in a cluttered, real-world environment requires solutions that tackle partial visibility and object novelty. Humans overcome this challenge with experience, which we emulate by developing a method to build a database of known 3D object models over time. We present an autonomous object registration pipeline deployed on a self-contained camera and robotic arm hardware system that produces 3D object point clouds. Experimentation evaluates the quantitative and qualitative aspects of the produced point clouds, and we show that our methods produce representations comparable with state-of-the-art methods. It is our hope that the solution presented in this thesis will aid in perception-based tasks that require identifying and interacting with objects in an unstructured environment."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120333"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Victoria Colthurst"],"dc:subject":["Robotics","Robot","Robots","3d","Three","Dimensions","Autonomous","Object","Model","Acquisition","Gripper","Grasp","Grasping","Geometric","Grasps","Geometry-based","Geometry","Registration","Point","Cloud","Clouds","Reconstruction","Cluttered","Rotation","Papras","Plug","Robotic","Depth","Scan","Scans"],"dc:title":["Autonomous object model acquisition with parallel jaw gripper"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}