SLAM Toolbox: SLAM for the dynamic world

Abstract

Previously existing open-source laser scanner SLAM algorithms available to users in the popular Robot Operating System (ROS) include GMapping, Karto, Cartographer, and Hector. However, few of these can build accurate maps of large spaces on the scale of the average Walmart store. Even fewer can do so in real-time using the mobile processor typically found in mobile robot systems today. The only package that could accomplish the above was Cartographer. However, it was abandoned by Google and it is no longer maintained. We propose a new fully open-source ROS package, SLAM Toolbox, to solve this problem. SLAM Toolbox builds on the legacy of Open Karto (Konolige et al., 2010), the open-source library from SRI International, providing not only accurate mapping algorithms, but a variety of other tools and improvements. SLAM Toolbox provides multiple modes of mapping depending on need, synchronous and asynchronous, utilities such as kinematic map merging, a localization mode, multi-session mapping, improved graph optimization, substantially reduced compute time, and prototype lifelong and distributed mapping applications.