In this work, we propose a method for large-scale topological localization based on radar scan images using learned descriptors. We present a simple yet efficient deep network architecture to compute a rotationally invariant discriminative global descriptor from a radar scan image. The performance and generalization ability of the proposed method is experimentally evaluated on two large scale driving datasets: MulRan and Oxford Radar RobotCar. Additionally, we present a comparative evaluation of radar-based and LiDAR-based localization using learned global descriptors. Our code and trained models are publicly available on the project website.
@article{arxiv.2110.03081,
title = {Large-Scale Topological Radar Localization Using Learned Descriptors},
author = {Jacek Komorowski and Monika Wysoczanska and Tomasz Trzcinski},
journal= {arXiv preprint arXiv:2110.03081},
year = {2021}
}