Appearance-Based Along-Route Localization for Planetary Missions

We propose an appearance-based along-route localization algorithm that relies on robust place recognition by matching image sequences instead of individual frames. Our approach extends state of the art place recognition framework SeqSLAM in several aspects to realize real-time localization along routes for autonomous navigation. First, our method is online in that we only rely on the recently observed image frames. Second, we provide a homing mechanism based on rotations computed from frame matches. And third, we use a more flexible mechanism to search for matching locations, not restricting the search to straight lines in the cost matrix as in SeqSLAM, but allowing for a wide variety of route traversal conditions such as varying velocities or rotational and translational viewpoint differences. We investigate different image preprocessing steps as well as image similarity metrics wrt. their influence on illumination and viewpoint invariance for a more robust place recognition. On a new challenging dataset, recorded in real world experiments with a planetary rover, in the course of a Moon-analogue mission on Sicily's Mount Etna, we show the feasibility of our direct, sequence-based approach to along-route localization.