Comparison of Visual SLAM Algorithms ORB-SLAM2, RTAB-Map and SPTAM in Internal and External Environments with ROS

This work compares three visual Simultaneous Localization and Mapping (vSLAM) algorithms: RTAB-Map, ORB-SLAM2 and SPTAM. Simulations were carried out in an indoor and an outdoor environment on gazebo using ROS (Robot Operating System). It was used a robot differential drive with RGB-D and stereo cam...

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Bibliographic Details
Published in:	2021 Latin American Robotics Symposium (LARS), 2021 Brazilian Symposium on Robotics (SBR), and 2021 Workshop on Robotics in Education (WRE) pp. 216 - 221
Main Authors:	de Jesus, Kesse Jonatas, Kobs, Henry Julio, Cukla, Anselmo Rafael, de Souza Leite Cuadros, Marco Antonio, Gamarra, Daniel Fernando Tello
Format:	Conference Proceeding
Language:	English
Published:	IEEE 11-10-2021
Subjects:	Cameras Heuristic algorithms Operating systems ORB SLAM Pose estimation Robot vision systems ROS RTAB SLAM Simultaneous localization and mapping SPTAM Visual SLAM Visualization
Online Access:	Get full text
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Summary:	This work compares three visual Simultaneous Localization and Mapping (vSLAM) algorithms: RTAB-Map, ORB-SLAM2 and SPTAM. Simulations were carried out in an indoor and an outdoor environment on gazebo using ROS (Robot Operating System). It was used a robot differential drive with RGB-D and stereo cameras in both scenarios. The efficiency of vSLAM methods is shown. As a result of the experiments, the S-PTAM showed a better performance in indoor and outdoor environment. The measures for the trajectory distance in the ORB-SLAM2 had more accuracy in an indoor environment and the RTAB-Map had more accuracy for measures of the trajectory distance in an outdoor environment with a stereo camera. The code of the project can be found at (https://github.com/Jhonan01/jhonan.git).
ISSN:	2643-685X
DOI:	10.1109/LARS/SBR/WRE54079.2021.9605432