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    Accurate On-Line 3D Occupancy Grids Using Manhattan World Constraints

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    Peasley12iros.pdf (3.854Mb)
    Date
    2012-10
    Author
    Peasley, Brian
    Birchfield, Stan
    Cunningham, Alexander
    Dellaert, Frank
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    Abstract
    In this paper we present an algorithm for constructing nearly drift-free 3D occupancy grids of large indoor environments in an online manner. Our approach combines data from an odometry sensor with output from a visual registration algorithm, and it enforces a Manhattan world constraint by utilizing factor graphs to produce an accurate online estimate of the trajectory of a mobile robotic platform. We also examine the advantages and limitations of the octree data structure representation of a 3D environment. Through several experiments in environments with varying sizes and construction we show that our method reduces rotational and translational drift significantly without performing any loop closing techniques.
    URI
    http://hdl.handle.net/1853/46286
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    • Computational Perception & Robotics [213]
    • Computational Perception & Robotics Publications [213]

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