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)
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
Subjects
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