Comparison of Visual SLAM Algorithms ORB-SLAM2, RTAB-Map and SPTAM in Internal and External Environments with ROS
Kesse Jonatas de Jesus, Henry Julio Kobs, Anselmo Rafael Cukla, Marco Antonio de Souza Leite Cuadros, Daniel Fernando Tello Gamarra
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).