Relocalization and Loop Closing in Vision Simultaneous Localization and Mapping (VSLAM) of a Mobile Robot Using ORB Method
Abstract
It is essential for a mobile robot during autonomous navigation to be able to detect revisited places or loop closures while performing Vision Simultaneous Localization And Mapping (VSLAM). Loop closing has been identified as one of the critical data association problem when building maps. It is an efficient way to eliminate errors and improve the accuracy of the robot localization and mapping. In order to solve loop closing problem, the ORB-SLAM algorithm, a feature based simultaneous localization and mapping system that operates in real time is used. This system includes loop closing and relocalization and allows automatic initialization.In order to check the performance of the algorithm, the monocular and stereo and RGB-D cameras are used. The aim of this thesis is to show the accuracy of relocalization and loop closing process using ORB SLAM algorithm in a variety of environmental settings. The performance of relocalization and loop closing in different challenging indoor scenarios are demonstrated by conducting various experiments. Experimental results show the applicability of the approach in real time application like autonomous navigation.
Degree
M.Sc.
Advisors
Houshangi, Purdue University.
Subject Area
Robotics|Artificial intelligence|Optics
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