Comparison of Visual SLAM Algorithms ORB-SLAM2, RTAB-Map and SPTAM in Internal and External Environments with ROS - Jesus, Kesse Jonatas de; Kobs, Henry Julio; Cukla, Anselmo Rafael; Cuadros, Marco Antonio de Souza Leite; Gamarra, Daniel Fernando Tello (Anais do Simpósio Brasileiro de Robótica e Simpósio Latino Americano de Robótica (SBR/LARS); 2021: Anais do XIII Simpósio Brasileiro de Robótica e XVIII Simpósio Latino Americano de Robótica, 2021)
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 ).