Benchmark of Visual SLAM Algorithms: ORB-SLAM2 vs RTAB-Map*

Abstract

This works deals with a benchmark of two well-known visual Simultaneous Localization and Mapping (vSLAM) algorithms: ORB-SLAM2 proposed by Mur-Atal & al in 2015 [7] and RTAB-Map proposed by [8]. The benchmark has been carried out with an Intel real-sense camera 435D mounted on top of a robotics electrical powered wheelchair running a ROS platform. The ORB SLAM has been implemented taking into account a monocular, stereo and RGB-D camera. RTAB SLAM, meanwhile, has only implemented with monocular and RGB-D camera. Several experiments have been carried out in a controlled indoor environment at the ESIGELEC's Autonomous Navigation Laboratory. These experiments are supported by the use of the VICON motion capture system used as a ground-truth to validate our results [1]. Different motion scenarios are used to test and benchmark the SLAM algorithms in various configurations: straight-line, straight-line and back, circular path with loop closure, etc.