A Constraint and Sampling-Based Approach to Integrated Task and Motion Planning

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dc.contributor.advisorChaudhuri, Swaraten_US
dc.contributor.committeeMemberKavraki, Lydia Een_US
dc.contributor.committeeMemberMcLurkin, Jamesen_US
dc.contributor.committeeMemberVardi, Moshe Ven_US
dc.creatorPrabhu, Sailesh Naveenaen_US
dc.date.accessioned2016-02-05T22:17:36Zen_US
dc.date.available2016-02-05T22:17:36Zen_US
dc.date.created2014-12en_US
dc.date.issued2014-09-30en_US
dc.date.submittedDecember 2014en_US
dc.date.updated2016-02-05T22:17:36Zen_US
dc.description.abstractThis thesis tackles the Integrated Task and Motion Planning (ITMP) Problem. The ITMP problem extends classical task planning with actions that require a motion plan. The agent seeks a sequence of actions and the necessary motions to achieve the goal. The user partially specifies the task plan by providing the actions' known parameters. An SMT solver, then, discovers values for the unkown parameters that satisfies constraints requiring the task plan to achieve the goal. The SMT solver utilizes an annotated Probabilistic Roadmap (PRM) to query for motion planning information. A sampling algorithm generates the PRM's vertices to permit a mobile manipulator to grasp numerous object configurations. Each iteration samples several base configurations and adds a base configuration to the PRM that increases the object configurations grasped from its vertices. Our results indicate that increasing the samples per iteration improves the probability the SMT solver discovers a satisfying assignment without adversely affecting the resulting task plan.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationPrabhu, Sailesh Naveena. "A Constraint and Sampling-Based Approach to Integrated Task and Motion Planning." (2014) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/88438">https://hdl.handle.net/1911/88438</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/88438en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectIntegrated Task and Motion Planningen_US
dc.subjectplanning from high-level specificationen_US
dc.subjectsynthesisen_US
dc.subjectconstraint-baseden_US
dc.subjectsampling-baseden_US
dc.titleA Constraint and Sampling-Based Approach to Integrated Task and Motion Planningen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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