Staff View
Compact representations for efficient robot motion planning with formal guarantees

Descriptive

TitleInfo
Title
Compact representations for efficient robot motion planning with formal guarantees
Name (type = personal)
NamePart (type = family)
Dobson
NamePart (type = given)
Andrew
NamePart (type = date)
1988-
DisplayForm
Andrew Dobson
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Bekris
NamePart (type = given)
Kostas E
DisplayForm
Kostas E Bekris
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Steiger
NamePart (type = given)
William
DisplayForm
William Steiger
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Yu
NamePart (type = given)
Jingjin
DisplayForm
Jingjin Yu
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Balkcom
NamePart (type = given)
Devin
DisplayForm
Devin Balkcom
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
DateOther (qualifier = exact); (type = degree)
2017-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
This work provides compact representations for single- and multi-robot motion planning in the context of prehensile robot manipulation. This work describes the asymptotic near-optimality and probabilistic near-optimality properties of these planners. Probabilistic near-optimality is leveraged to provide practical and grounded stopping criteria for these methods which probabilistically guarantee the methods return high-quality paths. It is also shown how these methods can be leveraged to produce a compact planning representation, which is a lightweight structure that is quick to query and easy to store. The work also outlines a compact representation for solving multi-arm manipulation tasks, and integrates a scalable, asymptotically optimal multi-robot motion planning method to provide scalable, globally asymptotically optimal task and motion planning in manipulation domains.
Subject (authority = RUETD)
Topic
Computer Science
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8356
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (ix, 162 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Robots--Motion
Subject (authority = ETD-LCSH)
Topic
Robots--Control systems
Note (type = statement of responsibility)
by Andrew Dobson
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T35X2D2K
Genre (authority = ExL-Esploro)
ETD doctoral
Back to the top

Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Dobson
GivenName
Andrew
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-09-17 17:12:10
AssociatedEntity
Name
Andrew Dobson
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
CreatingApplication
Version
1.5
ApplicationName
pdfTeX-1.40.14
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2017-09-03T15:40:38
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2017-09-03T15:40:38
Back to the top
Version 8.5.5
Rutgers University Libraries - Copyright ©2024