{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/100627"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/100627","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Hierarchical planning for multi-contact non-prehensile manipulation","abstract":"Manipulation planning involves planning the combined motion of objects in the environment as well as the robot motions to achieve them. Ideally, we would like to be able to plan prehensile and non-prehensile manipulation in an integrated fashion, but despite much progress in planning motions in the robot's configuration space in the presence of obstacles, progress in general manipulation planning has been more limited. The manipulation planning problem has a number of complicating factors, including the large dimensionality of the combined space. In this thesis, we explore a hierarchical approach to planning sequences of non-prehensile and prehensile actions. We subdivide the planning problem in three stages (object contacts, object poses and robot contacts) and thereby reduce the size of search space that is explored. We show that this approach is more efficient than earlier strategies that search in the combined robot-object configuration space directly.","abstract_html":"Manipulation planning involves planning the combined motion of objects in the environment as well as the robot motions to achieve them. Ideally, we would like to be able to plan prehensile and non-prehensile manipulation in an integrated fashion, but despite much progress in planning motions in the robot's configuration space in the presence of obstacles, progress in general manipulation planning has been more limited. The manipulation planning problem has a number of complicating factors, including the large dimensionality of the combined space. In this thesis, we explore a hierarchical approach to planning sequences of non-prehensile and prehensile actions. We subdivide the planning problem in three stages (object contacts, object poses and robot contacts) and thereby reduce the size of search space that is explored. We show that this approach is more efficient than earlier strategies that search in the combined robot-object configuration space directly.","abstract_has_math":false,"creators":["Lee, Gilwoo"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Tomás Lozano-Pérez and Leslie Pack Kaelbling."],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-22T22:21:37Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/100627","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Tomás Lozano-Pérez and Leslie Pack Kaelbling."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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The certified thesis is available in the Institute Archives and Special Collections.","Cataloged from student-submitted PDF version of thesis.","Includes bibliographical references (pages 34-35)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Manipulation planning involves planning the combined motion of objects in the environment as well as the robot motions to achieve them. Ideally, we would like to be able to plan prehensile and non-prehensile manipulation in an integrated fashion, but despite much progress in planning motions in the robot's configuration space in the presence of obstacles, progress in general manipulation planning has been more limited. The manipulation planning problem has a number of complicating factors, including the large dimensionality of the combined space. In this thesis, we explore a hierarchical approach to planning sequences of non-prehensile and prehensile actions. We subdivide the planning problem in three stages (object contacts, object poses and robot contacts) and thereby reduce the size of search space that is explored. We show that this approach is more efficient than earlier strategies that search in the combined robot-object configuration space directly."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M. Eng."]},{"key":"dc:title","label":"Title","values":["Hierarchical planning for multi-contact non-prehensile manipulation"]}]}],"canonical_facts":{"dc:contributor.advisor":["Tomás Lozano-Pérez and Leslie Pack Kaelbling."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. 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Ideally, we would like to be able to plan prehensile and non-prehensile manipulation in an integrated fashion, but despite much progress in planning motions in the robot's configuration space in the presence of obstacles, progress in general manipulation planning has been more limited. The manipulation planning problem has a number of complicating factors, including the large dimensionality of the combined space. In this thesis, we explore a hierarchical approach to planning sequences of non-prehensile and prehensile actions. We subdivide the planning problem in three stages (object contacts, object poses and robot contacts) and thereby reduce the size of search space that is explored. We show that this approach is more efficient than earlier strategies that search in the combined robot-object configuration space directly."],"dc:description.degree":["M. 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