Experimental evaluation of ROS compatible SLAM algorithms for RGB-D sensors

Abstract

The recent adoption of the Robot Operating System (ROS) as a software standard in robotics has contributed to novel solutions for several problems on the area. One such problem is known as Simultaneous Localization and Mapping (SLAM), for which a number of algorithms from different classes are available as ROS packages ready to be used on any compatible robot. Considering that there is often a need to evaluate and choose an appropriate solution in any robotics application, this work presents an experimental evaluation of five SLAM algorithms usable on RGB-D sensors, namely, Gmapping, Hector SLAM, ORB SLAM, ORB SLAM 2 and RTAB-Map. The algorithms are assessed on data depicting realistic operation scenarios according to established criteria enumerated to emphasize practical aspects of the selected systems. The experiences reported on this work should provide insight for roboticists seeking a SLAM solution for indoor applications.