ReFeree: Radar-based efficient global descriptor using a Feature and Free space for Place Recognition

TL;DR

This paper introduces ReFeree, a lightweight radar-based descriptor leveraging feature and free space information, improving place recognition robustness in adverse weather conditions.

Contribution

The paper presents a novel radar descriptor called ReFeree that effectively summarizes radar images, capturing semi-metric information for enhanced place recognition performance.

Findings

Effective in adverse weather conditions

Validated on multiple datasets including MulRan and Oxford Radar datasets

Lightweight with strong place recognition capabilities

Abstract

Radar is highlighted for robust sensing capabilities in adverse weather conditions (e.g. dense fog, heavy rain, or snowfall). In addition, Radar can cover wide areas and penetrate small particles. Despite these advantages, Radar-based place recognition remains in the early stages compared to other sensors due to its unique characteristics such as low resolution, and significant noise. In this paper, we propose a Radarbased place recognition utilizing a descriptor called ReFeree using a feature and free space. Unlike traditional methods, we overwhelmingly summarize the Radar image. Despite being lightweight, it contains semi-metric information and is also outstanding from the perspective of place recognition performance. For concrete validation, we test a single session from the MulRan dataset and a multi-session from the Oxford Offroad Radar, Oxford Radar RobotCar, and the Boreas dataset.