{"id":{"repo_id":"rice","oai_identifier":"oai:repository.rice.edu:1911/103619"},"canonical_url":"https://search.dev.ndltd.org/etd/rice/oai:repository.rice.edu:1911/103619","repository":{"repo_id":"rice","name":"Rice University","base_url":"https://repository.rice.edu/server/oai/request"},"display":{"title":"Kinodynamic motion planning for high-dimensional physical systems","abstract":"This thesis presents a kinodynamic motion planner, Kinodynamic Motion Planning by Interior-Exterior Cell Exploration ( KPIECE ), specifically designed for systems with complex dynamics, where physics-based simulation is necessary. A multiple-level grid-based discretization is used to estimate the coverage of the state space. The coverage estimates help the planner detect the less explored areas of the state space. The planner also keeps track of the boundary of the explored region of the state space and focuses exploration on the less covered parts of this boundary. Extensive experiments show KPIECE provides computational gain over state-of-the-art methods and allows solving some harder, previously unsolvable problems. A shared memory parallel implementation is presented as well. This implementation provides better speedup than an embarrassingly parallel implementation by taking advantage of the evolving multi-core technology.","abstract_html":"This thesis presents a kinodynamic motion planner, Kinodynamic Motion Planning by Interior-Exterior Cell Exploration ( KPIECE ), specifically designed for systems with complex dynamics, where physics-based simulation is necessary. A multiple-level grid-based discretization is used to estimate the coverage of the state space. The coverage estimates help the planner detect the less explored areas of the state space. The planner also keeps track of the boundary of the explored region of the state space and focuses exploration on the less covered parts of this boundary. Extensive experiments show KPIECE provides computational gain over state-of-the-art methods and allows solving some harder, previously unsolvable problems. A shared memory parallel implementation is presented as well. This implementation provides better speedup than an embarrassingly parallel implementation by taking advantage of the evolving multi-core technology.","abstract_has_math":false,"creators":["Sucan, Ioan Alexandru"],"institution":"Rice University","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Kavraki, Lydia E."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-24T04:10:36Z","subjects":["Computer science","Applied sciences"],"languages":["eng"],"rights":["Copyright is held by the author, unless otherwise indicated. 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