{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/125573"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/125573","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Dynamic and structured scene representation for robotic manipulation","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_has_math":false,"creators":["Wang, Yixuan"],"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":["Li, Yunzhu","Driggs-Campbell, Katie","Hajek, Bruce"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-07-19","date_published":"2024-07-19","updated_at":"2026-07-22T22:25:02Z","subjects":["Robotic Manipulation","Robot Learning","Representation Learning"],"languages":["en","eng"],"rights":["Copyright 2024 Yixuan Wang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/125573","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Li, Yunzhu","Driggs-Campbell, Katie","Hajek, Bruce"]},{"key":"dc:creator","label":"Author","values":["Wang, Yixuan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-07-19","2024-08"]},{"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":["Robotic Manipulation","Robot Learning","Representation Learning"]}]},{"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 2024 Yixuan Wang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/125573"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Yixuan Wang, accepted the attached license on 2024-07-18 at 16:03.","The student, Yixuan Wang, submitted this Thesis for approval on 2024-07-18 at 16:11.","This Thesis was approved for publication on 2024-07-19 at 11:50.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20967 on 2025-02-04 at 21:04:18","Representation is an essential component of typical robotic manipulation frameworks. An ideal representation should be both efficient for computation and sufficient for downstream tasks. However, existing representations typically have fixed dimensions, which may not be optimal for different tasks. Therefore, in the first part of the thesis, we propose a dynamic representation that can dynamically adapt its dimensions to current the observation and the goal. Through various pile manipulation experiments, we demonstrate that dynamic representation can significantly improve the performance of robotic manipulation tasks compared to fixed- size representations. In the second part of the thesis, we propose another novel implicit representation, D$^3$Fields, that is 3D, semantic, and dynamic. Such a representation can be used for zero-shot generalizable rearrangement tasks, where the goal is specified by 2D images. We demonstrate the effectiveness of our D$^3$Fields through a wide range of robotic rearrangement tasks, including organizing shoes, collecting debris, and organizing office desks. Compared to state-of-the-art implicit 3D representations, such as FeatureNeRF and DistilledNeRF [1], [2], our D$^3$Fields is more computationally efficient and effective for novel scenes."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Dynamic and structured scene representation for robotic manipulation"]}]}],"canonical_facts":{"dc:contributor":["Li, Yunzhu","Driggs-Campbell, Katie","Hajek, Bruce"],"dc:creator":["Wang, Yixuan"],"dc:date":["2024-07-19","2024-08"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Yixuan Wang, accepted the attached license on 2024-07-18 at 16:03.","The student, Yixuan Wang, submitted this Thesis for approval on 2024-07-18 at 16:11.","This Thesis was approved for publication on 2024-07-19 at 11:50.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20967 on 2025-02-04 at 21:04:18","Representation is an essential component of typical robotic manipulation frameworks. An ideal representation should be both efficient for computation and sufficient for downstream tasks. However, existing representations typically have fixed dimensions, which may not be optimal for different tasks. Therefore, in the first part of the thesis, we propose a dynamic representation that can dynamically adapt its dimensions to current the observation and the goal. Through various pile manipulation experiments, we demonstrate that dynamic representation can significantly improve the performance of robotic manipulation tasks compared to fixed- size representations. In the second part of the thesis, we propose another novel implicit representation, D$^3$Fields, that is 3D, semantic, and dynamic. Such a representation can be used for zero-shot generalizable rearrangement tasks, where the goal is specified by 2D images. We demonstrate the effectiveness of our D$^3$Fields through a wide range of robotic rearrangement tasks, including organizing shoes, collecting debris, and organizing office desks. Compared to state-of-the-art implicit 3D representations, such as FeatureNeRF and DistilledNeRF [1], [2], our D$^3$Fields is more computationally efficient and effective for novel scenes."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/125573"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Yixuan Wang"],"dc:subject":["Robotic Manipulation","Robot Learning","Representation Learning"],"dc:title":["Dynamic and structured scene representation for robotic manipulation"],"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":"2026-07-22T22:25:02Z"}