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Global indoor 2D localization using polygon edge visibility decomposition
Descriptive
TitleInfo
Title
Global indoor 2D localization using polygon edge visibility decomposition
Name
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Isaacs
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Jeffrey
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Jeffrey Isaacs
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author
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Sarwate
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Anand
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Anand D Sarwate
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Advisory Committee
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chair
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Dana
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Kristin
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Kristin Dana
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Advisory Committee
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member
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Hadzic
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Ilija
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Ilija Hadzic
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Advisory Committee
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member
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Hobby
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John D
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John D Hobby
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Advisory Committee
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Rutgers University
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degree grantor
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School of Graduate Studies
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theses
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2023
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2023-01
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2023
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English
Abstract
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In their 1995 paper titled The Robot Localization Problem, Guibas, Motwani, andRaghavan present an idealized method for localizing a mobile robot equipped with a LiDAR and compass in a polygonal map. By constructing a notion of equivalence between visibility polygons, a partition on the map is formed by grouping related points into polygonal visibility cells, which are then organized into a searchable data structure. In this thesis, we make a series of modifications to their approach that makes it suitable for use in a live robotic system, accounting for angular uncertainty, sensor noise, and occlusions in the map. Rather than searching for exact correspondences, we build a robust fingerprint for each visibility cell by recording its set of visible map edges parametrized by (r, θ) pairs. When a query LiDAR scan is received, the lines in the LiDAR image are extracted and an approximate visibility fingerprint is constructed. By using the (r, θ) parametrization, we compress the search space, and decouple the 3 degrees of freedom search into a series of simpler 1D correlations. We then present the output and runtime of our implementation on a number of synthetic maps with added sensor noise and occlusions to demonstrate its viability in a live system.
Subject
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Topic
Computer engineering
Subject
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Topic
2D
Subject
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Topic
Global
Subject
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Topic
Indoor
Subject
(authority = local)
Topic
Localization
Subject
(authority = local)
Topic
Polygon
Subject
(authority = local)
Topic
Visibility
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Title
Rutgers University Electronic Theses and Dissertations
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http://dissertations.umi.com/gsnb.rutgers:12287
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text/xml
Extent
68 pages : illustrations
Note
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M.S.
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier
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doi:10.7282/t3-b017-m850
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
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Isaacs
GivenName
Jeffrey
MiddleName
J
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Permission or license
DateTime
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2023-02-23T12:18:25
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Jeffrey J Isaacs
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Affiliation
Rutgers University. School of Graduate Studies
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License
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Author Agreement License
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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
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