Long-term Large-scale Mapping and Localization Using maplab

Abstract

This paper discusses a large-scale and long-term mapping and localization scenario using the maplab open-source framework. We present a brief overview of the specific algorithms in the system that enable building a consistent map from multiple sessions. We then demonstrate that such a map can be reused even a few months later for efficient 6-DoF localization and also new trajectories can be registered within the existing 3D model. The datasets presented in this paper are made publicly available.

Workshop on Long-term autonomy and deployment of intelligent robots in the real-world, ICRA 2018, Brisbane, Australia