A Comparison of Modern General-Purpose Visual SLAM Approaches

TL;DR

This paper compares three modern visual SLAM systems—ORB-SLAM3, OpenVSLAM, and RTABMap—across multiple datasets to evaluate their suitability for diverse robotic applications in various environments.

Contribution

It provides the first comprehensive benchmark comparison of these three feature-rich, robust VSLAM systems across multiple datasets and domains, highlighting their strengths and limitations.

Findings

ORB-SLAM3 and OpenVSLAM outperform RTABMap in several datasets.

All three systems demonstrate robustness across indoor and outdoor environments.

The study offers insights into their integration potential with ROS 2 Nav2.

Abstract

Advancing maturity in mobile and legged robotics technologies is changing the landscapes where robots are being deployed and found. This innovation calls for a transformation in simultaneous localization and mapping (SLAM) systems to support this new generation of service and consumer robots. No longer can traditionally robust 2D lidar systems dominate while robots are being deployed in multi-story indoor, outdoor unstructured, and urban domains with increasingly inexpensive stereo and RGB-D cameras. Visual SLAM (VSLAM) systems have been a topic of study for decades and a small number of openly available implementations have stood out: ORB-SLAM3, OpenVSLAM and RTABMap. This paper presents a comparison of these 3 modern, feature rich, and uniquely robust VSLAM techniques that have yet to be benchmarked against each other, using several different datasets spanning multiple domains negotiated by service robots. ORB-SLAM3 and OpenVSLAM each were not compared against at least one of these datasets previously in literature and we provide insight through this lens. This analysis is motivated to find general purpose, feature complete, and multi-domain VSLAM options to support a broad class of robot applications for integration into the new and improved ROS 2 Nav2 System as suitable alternatives to traditional 2D lidar solutions.