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        <identifier>oai:www.ideals.illinois.edu:2142/34217</identifier>
        <datestamp>2023-07-10</datestamp>
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        <thesis xmlns="http://www.ndltd.org/standards/metadata/etdms/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.ndltd.org/standards/metadata/etdms/1.1/ http://www.ndltd.org/standards/metadata/etdms/1.1/etdms11.xsd http://purl.org/dc/elements/1.1/ http://www.ndltd.org/standards/metadata/etdms/1.1/etdmsdc.xsd">
          <dc:contributor>Chung, Soon-Jo</dc:contributor>
          <dc:contributor>Hutchinson, Seth A.</dc:contributor>
          <dc:creator>Rao, Dushyant</dc:creator>
          <dc:date>2012-09-18T21:06:20Z</dc:date>
          <dc:date>2012-09-18T21:06:20Z</dc:date>
          <dc:date>2012-08</dc:date>
          <dc:date>2012-09-18T21:06:20Z</dc:date>
          <dc:date>2012-08</dc:date>
          <dc:description>Existing approaches to visual Simultaneous Localization and Mapping (SLAM)
typically utilize points as visual feature primitives to represent landmarks in the
environment. Since these techniques mostly use image points from a standard
feature point detector, they do not explicitly map objects or regions of interest.
Further, previous SLAM techniques that propose the use of higher level structures
often place constraints on the environment, such as requiring orthogonal lines and
planes. Our work is motivated by the need for different SLAM techniques in path
and riverine settings, where feature points can be scarce and may not adequately
represent the environment. Accordingly, the proposed approach uses B´ezier polynomial
curves as stereo vision primitives and offers a novel SLAM formulation to
update the curve parameters and vehicle pose. This method eliminates the need
for point-based stereo matching, with an optimization procedure to directly extract
the curve information in the world frame from noisy edge measurements.
Further, the proposed algorithm enables navigation with fewer feature states than
most point-based techniques, and is able to produce a map which only provides
detail in key areas. Results in simulation and with vision data validate that the
proposed method can be effective in estimating the 6DOF pose of the stereo camera,
and can produce structured, uncluttered maps. Monte Carlo simulations of
the algorithm are also provided to analyze its consistency.</dc:description>
          <dc:description>Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-07-19T14:24:46Z
Item was in collections:
University of Illinois Theses &amp; Dissertations (ID: 1)
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          <dc:identifier>http://hdl.handle.net/2142/34217</dc:identifier>
          <dc:language>en</dc:language>
          <dc:rights>Copyright 2012 Dushyant Rao</dc:rights>
          <dc:subject>Robotics</dc:subject>
          <dc:subject>SLAM</dc:subject>
          <dc:subject>Computer Vision</dc:subject>
          <dc:subject>Micro Aerial Vehicles</dc:subject>
          <dc:subject>Visual Navigation</dc:subject>
          <dc:title>CurveSLAM: utilizing higher level structure in stereo vision-based navigation</dc:title>
          <degree>
            <department>Aerospace Engineering</department>
            <departmentCode>1615</departmentCode>
            <discipline>Aerospace Engineering</discipline>
            <disciplineCode>4048</disciplineCode>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <level>Thesis</level>
            <name>M.S.</name>
            <program>MS: Aerospace Engr -UIUC</program>
            <programCode>10KS4048MS</programCode>
          </degree>
        </thesis>
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