Title
Comparison of Visual SLAM Algorithms ORB-SLAM2, RTAB-Map and SPTAM in Internal and External Environments with ROS
Date Issued
01 January 2021
Access level
metadata only access
Resource Type
conference paper
Author(s)
De Jesus K.J.
Kobs H.J.
Cukla A.R.
De Souza Leite Cuadros M.A.
Universidade Federal de Santa Maria-Santa Maria
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
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).
Start page
216
End page
221
Language
English
OCDE Knowledge area
Sistemas de automatización, Sistemas de control Ciencias de la computación
Scopus EID
2-s2.0-85123468598
ISBN
9781665407618
ISBN of the container
978-166540761-8
DOI of the container
10.1109/LARS/SBR/WRE54079.2021.9605432
Conference
2021 Latin American Robotics Symposium, 2021 Brazilian Symposium on Robotics, and 2021 Workshop on Robotics in Education, LARS-SBR-WRE 2021
Sources of information: Directorio de Producción Científica Scopus