Active perception in visual simultaneous localization and mapping by feature / map point selection
Shangguan, Zhenghe
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https://hdl.handle.net/2142/106391
Description
Title
Active perception in visual simultaneous localization and mapping by feature / map point selection
Author(s)
Shangguan, Zhenghe
Issue Date
2019-12-11
Director of Research (if dissertation) or Advisor (if thesis)
Bretl, Timothy W.
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)
SLAM
Computer Vision
Active Perception
Feature Selection
Map Point Selection
Mobile Robotics
Abstract
One traditional and typical method to improve the computational efficiency of Visual Simultaneous Localization and Mapping (Visual SLAM) is selecting features which hold most contributions in estimating the pose in Tracking thread of SLAM. In this thesis, we first analyze the disadvantages of some most recent feature selection algorithms by adapting them onto ORB-SLAM2, then present a brand-new map point selection algorithm which significantly enhances the efficiency, while avoids some disadvantages in feature selection as well as keeps the accuracy at the same level. Finally, we test our map point selection algorithm on standard datasets with ORB-SLAM2 and analyze the performance improvement.
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