Please use this identifier to cite or link to this item:
Title: ORB-SLAM-based 2D Reconstruction of Environment for Indoor Autonomous Navigation of UAVs
Authors: Yusefi, Abdullah
Durdu, Akif
Sungur, Cemil
Issue Date: 2020
Abstract: In this paper, a simple and economic yet efficient autonomous mapping and navigation system for unmanned aerial vehicles is presented. In order to realize this system, three modules have been implemented. First module constructs a 3D model of the environment while autonomously navigating the drone and is based on one of the top monocular SLAM algorithms called ORB- SLAM. For the autonomous navigation of the system a visual-based line tracking method is proposed. Afterwards, the second module performs a real time transformation of the 3D map to 2D grid map. While most of the 3D to 2D map conversion studies use octomaps in the middle of two, we present a threshold-based method that directly converts the 3D map to 2D without need for any middle component. Finally, third module uses A* path planning algorithm to navigate the drone to the goal pose in the constructed 2D grid map. This module uses only IMU-aided Adaptive Monte Carlo localization (AMCL) combined with monocular camera information to complete this task. The experimentation results indicate that the proposed system is adequately efficient to be used in the low-cost drones that have only a monocular camera and limited processing resources on them.
ISSN: 2148-2683
Appears in Collections:TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collections

Files in This Item:
File SizeFormat 
10.31590-ejosat.819620-1374874.pdf831.53 kBAdobe PDFView/Open
Show full item record

CORE Recommender

Page view(s)

checked on Sep 25, 2023


checked on Sep 25, 2023

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.