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Autonomous mobile robot navigation with GPU acceleration for unmanned UV-C based decontamination applications

Descriptive

TitleInfo
Title
Autonomous mobile robot navigation with GPU acceleration for unmanned UV-C based decontamination applications
Name (type = personal)
NamePart (type = family)
Vachhani
NamePart (type = given)
Birju
NamePart (type = date)
1992-
DisplayForm
Birju Vachhani
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Zou
NamePart (type = given)
Qingze
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Qingze Zou
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Advisory Committee
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chair
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NamePart (type = family)
Bai
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Xiaoli
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Xiaoli Bai
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Advisory Committee
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internal member
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Mazzeo
NamePart (type = given)
Aaron
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Aaron Mazzeo
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Advisory Committee
Role
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internal 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)
2019
DateOther (qualifier = exact); (type = degree)
2019-01
CopyrightDate (encoding = w3cdtf)
2019
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Navigation is a complex robotic problem solving which makes the mobile robot intelligent for decision making in dynamic environments. The objective of this thesis is to achieve autonomous mapping and navigation of a 2D environment for unmanned decontamination and sterilization of rooms in facilities such as hospitals and hotels, where UV-based degermination system is carried by a four-wheeled robot during the navigation. The challenge arises from the intensive online computation needed in the navigation process, as a Light Detection and Ranging (LiDAR) system is employed for Simultaneous Localization and Mapping (SLAM) and obstacle detection, and occupancy grid is employed as the data structure to represent surrounding environments in robotics. However, path planning on an occupancy grid is computationally intensive. For example, path planning on a 25m x 25m grid can involve processing of 250,000 grid cells on a 0.05m resolution grid. In this project, we developed a parallel computation framework to substantially reduce the processing times, and thereby, achieve dynamic obstacle avoidance and autonomous exploration. Specifically, a obstacle inflation module was created using parallel computing. Building on that, a graph based path planner was also developed for autonomous as well as user instructed navigation. The system was thoroughly tested in various static and dynamic indoor environments.
Subject (authority = RUETD)
Topic
Mechanical and Aerospace Engineering
Subject (authority = ETD-LCSH)
Topic
Robots--Motion
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_9456
PhysicalDescription
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electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (65 pages) : illustrations
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Birju Jitendra Vachhani
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-hc0y-xj46
Genre (authority = ExL-Esploro)
ETD graduate
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Vachhani
GivenName
Birju
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2018-12-21 12:10:24
AssociatedEntity
Name
Birju Vachhani
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.
RightsEvent
Type
Embargo
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-01-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2020-01-31
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after January 31st, 2020.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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ETD
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windows xp
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DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2019-01-17T16:12:38
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2019-01-17T16:12:38
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pdfTeX-1.40.18
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