Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras

Abstract

To enable long term exploration of extreme environments such as planetary surfaces, heterogeneous robotic teams need the ability to localize themselves on previously built maps. While the Localization and Mapping problem for single sessions can be efficiently solved with many state of the art solutions, place recognition in natural environments still poses great challenges for the perception system of a robotic agent. In this paper we propose a relocalization pipeline which exploits both 3D and visual information from stereo cameras to detect matches across local point clouds of multiple SLAM sessions. Our solution is based on a Bag of Binary Words scheme where binarized SHOT descriptors are enriched with visual cues to recall in a fast and efficient way previously visited places. The proposed relocalization scheme is validated on challenging datasets captured using a planetary rover prototype on Mount Etna, designated as a Moon analogue environment.