Title:
Navigation among movable obstacles in unknown environments

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dc.contributor.advisor Stilman, Mike
dc.contributor.author Levihn, Martin en_US
dc.contributor.committeeMember Mynatt, Elizabeth D.
dc.contributor.committeeMember Bell, Genevieve
dc.contributor.committeeMember Foley, James
dc.contributor.committeeMember Forlizzi, Jodi
dc.contributor.department Computing en_US
dc.date.accessioned 2011-07-06T16:47:47Z
dc.date.available 2011-07-06T16:47:47Z
dc.date.issued 2011-04-05 en_US
dc.description.abstract This work presents a new class of algorithms that extend the domain of Navigation Among Movable Obstacles (NAMO) to unknown environments. Efficient real-time algorithms for solving NAMO problems even when no initial environment information is available to the robot are presented and validated. The algorithms yield optimal solutions and are evaluated for real-time performance on a series of simulated domains with more than 70 obstacles. In contrast to previous NAMO algorithms that required a pre-specified environment model, this work considers the realistic domain where the robot is limited by its sensor range. It must navigate to a goal position in an environment of static and movable objects. The robot can move objects if the goal cannot be reached or if moving the object significantly shortens the path. The robot gains information about the world by bringing distant objects into its sensor range. The first practical planner for this exponentially complex domain is presented. The planner reduces the search-space through a collection of techniques, such as upper bound calculations and the maintenance of sorted lists with underestimates. Further, the algorithm is only considering manipulation actions if these actions are creating a new opening in the environment. In the addition to the evaluation of the planner itself is each of this techniques also validated independently. en_US
dc.description.degree M.S. en_US
dc.identifier.uri http://hdl.handle.net/1853/39559
dc.publisher Georgia Institute of Technology en_US
dc.subject Moption planning en_US
dc.subject Path planning en_US
dc.subject.lcsh Algorithms
dc.subject.lcsh Robotics
dc.subject.lcsh Personal robotics
dc.subject.lcsh Robots
dc.title Navigation among movable obstacles in unknown environments en_US
dc.type Text
dc.type.genre Thesis
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
local.contributor.corporatename School of Computer Science
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
relation.isOrgUnitOfPublication 6b42174a-e0e1-40e3-a581-47bed0470a1e
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