{"id":{"repo_id":"gatech","oai_identifier":"oai:repository.gatech.edu:1853/66535"},"canonical_url":"https://search.dev.ndltd.org/etd/gatech/oai:repository.gatech.edu:1853/66535","repository":{"repo_id":"gatech","name":"Georgia Tech","base_url":"https://repository.gatech.edu/server/oai/request"},"display":{"title":"INFORMED EXPLORATION ALGORITHMS FOR ROBOT MOTION PLANNING AND LEARNING","abstract":"Sampling-based methods have emerged as a promising technique for solving robot motion-planning problems. These algorithms avoid a priori discretization of the search-space by generating random samples and building a graph online. While the recent advances in this area endow these randomized planners with asymptotic optimality, their slow convergence rate still remains a challenge. One of the reasons for this poor performance can be traced to the widely used uniform sampling strategy that naively explores the entire search-space. Having access to an intelligent exploration strategy that can focus search, would alleviate one of the critical bottlenecks in speeding up these algorithms. This thesis endeavors to tackle this problem by presenting exploration algorithms that leverage different sources of information available during planning time.","abstract_html":"Sampling-based methods have emerged as a promising technique for solving robot motion-planning problems. These algorithms avoid a priori discretization of the search-space by generating random samples and building a graph online. While the recent advances in this area endow these randomized planners with asymptotic optimality, their slow convergence rate still remains a challenge. One of the reasons for this poor performance can be traced to the widely used uniform sampling strategy that naively explores the entire search-space. Having access to an intelligent exploration strategy that can focus search, would alleviate one of the critical bottlenecks in speeding up these algorithms. This thesis endeavors to tackle this problem by presenting exploration algorithms that leverage different sources of information available during planning time.","abstract_has_math":false,"creators":["Joshi, Sagar Suhas"],"institution":"Georgia Institute of Technology","degree_name":null,"degree_level":"Doctoral","degree_discipline":null,"degree_department":"Aerospace Engineering","school":null,"contributors":[],"advisors":["Tsiotras, Panagiotis"],"committee_chairs":[],"committee_members":["Hutchinson, Seth","Gombolay, Matthew","Ravichandar, Harish","Boots, Byron"],"year":2022,"date_issued":"2022-05-03","date_published":"2022-05-03","updated_at":"2026-07-27T19:49:09Z","subjects":["Robotics","Motion Planning","Learning for Robotics"],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1853/66535","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Tsiotras, Panagiotis"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Hutchinson, Seth","Gombolay, Matthew","Ravichandar, Harish","Boots, Byron"]},{"key":"dc:contributor.department","label":"Department","values":["Aerospace Engineering"]},{"key":"dc:creator","label":"Author","values":["Joshi, Sagar Suhas"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-05-18T19:30:08Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-05-18T19:30:08Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-05-03"]},{"key":"dc:publisher","label":"Institution","values":["Georgia Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Robotics","Motion Planning","Learning for Robotics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1853/66535"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Sampling-based methods have emerged as a promising technique for solving robot motion-planning problems. 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