{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/130069"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/130069","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Subdimensional expansion method for multi-agent path finding with long narrow corridors","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01","abstract_has_math":false,"creators":["You, Haoyuan"],"institution":"University of Illinois Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Driggs-Campbell, Katie"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-07-25","date_published":"2025-07-25","updated_at":"2026-07-22T22:25:06Z","subjects":["Multi-agent Path Finding","Robotics"],"languages":["en","eng"],"rights":["Copyright 2025 Haoyuan You"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/130069","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Driggs-Campbell, Katie"]},{"key":"dc:creator","label":"Author","values":["You, Haoyuan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-07-25","2025-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"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 Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Multi-agent Path Finding","Robotics"]}]},{"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 2025 Haoyuan You"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/130069"]}]},{"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 2027-08-01","The student, Haoyuan You, accepted the attached license on 2025-07-24 at 20:31.","The student, Haoyuan You, submitted this Thesis for approval on 2025-07-24 at 20:41.","This Thesis was approved for publication on 2025-07-25 at 09:27.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22732 on 2025-10-21 at 10:06:21","Multi-agent path finding, a problem largely related to the field of robotics, has been proven to be an NP-Hard problem and computationally heavy. Experience-based planning method is a sample-based method that uses a pre-computed database to reduce the planning time. We propose an algorithm that extends based on a prior experience-based framework to target specifically multi-agent path planning problems with long narrow corridors. By leveraging graph homomorphism, we expand a database for doorway problems to cover corridors with various shapes and sizes. The algorithm can find solutions for MAPF problems with a consistent 60-70% higher success rate compared to multiple baselines in environments with multiple narrow corridors without sacrificing performance. The proposed algorithm shows the ability to plan the paths for about a hundred robots in congested simulated environments with and without narrow corridors within a few seconds."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Subdimensional expansion method for multi-agent path finding with long narrow corridors"]}]}],"canonical_facts":{"dc:contributor":["Driggs-Campbell, Katie"],"dc:creator":["You, Haoyuan"],"dc:date":["2025-07-25","2025-08"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01","The student, Haoyuan You, accepted the attached license on 2025-07-24 at 20:31.","The student, Haoyuan You, submitted this Thesis for approval on 2025-07-24 at 20:41.","This Thesis was approved for publication on 2025-07-25 at 09:27.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22732 on 2025-10-21 at 10:06:21","Multi-agent path finding, a problem largely related to the field of robotics, has been proven to be an NP-Hard problem and computationally heavy. Experience-based planning method is a sample-based method that uses a pre-computed database to reduce the planning time. We propose an algorithm that extends based on a prior experience-based framework to target specifically multi-agent path planning problems with long narrow corridors. By leveraging graph homomorphism, we expand a database for doorway problems to cover corridors with various shapes and sizes. The algorithm can find solutions for MAPF problems with a consistent 60-70% higher success rate compared to multiple baselines in environments with multiple narrow corridors without sacrificing performance. The proposed algorithm shows the ability to plan the paths for about a hundred robots in congested simulated environments with and without narrow corridors within a few seconds."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/130069"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Haoyuan You"],"dc:subject":["Multi-agent Path Finding","Robotics"],"dc:title":["Subdimensional expansion method for multi-agent path finding with long narrow corridors"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:06Z"}