Monocular vision based navigation using image moments of polygonal features
Ma, Lingyu
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https://hdl.handle.net/2142/95582
Description
Title
Monocular vision based navigation using image moments of polygonal features
Author(s)
Ma, Lingyu
Issue Date
2016-11-23
Director of Research (if dissertation) or Advisor (if thesis)
Hutchinson, Seth
Chung, Soon-Jo
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Simultaneous localization and mapping (SLAM)
Vision-based navigation
Abstract
This thesis presents a novel monocular-vision-based localization and mapping algorithm using moments of polygon features. The landmarks we use are polygonal regions instead of a dense set of feature points, which can significantly reduce the computational complexity of data association and produce a map that is geometrically and structurally more meaningful. Each region can be characterized using its depth and orientation with respect to the camera and an polygon detection and tracking algorithm is developed. The monocular vision Simultaneous Localization and Mapping (SLAM) problem is formulated as a filter problem to incorporate the image moments of the close regions or polygons tracked. The observability of the SLAM estimator is further improved by both the additional measurements with respect to the initial view location and the use of image moments. We analyze the performance of our SLAM algorithm with numerical simulations and experimental results. We also compared our results with ORB-SLAM to show the effectiveness of our algorithm in outdoor environments.
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