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AutoPlace: Robust Place Recognition with Low-cost Single-chip Automotive Radar

2021-09-17 17:16:09
Kaiwen Cai, Bing Wang, Chris Xiaoxuan Lu
arXiv_RO
           
Abstract

This paper presents a novel place recognition approach to autonomous vehicles by using low-cost, single-chip automotive radar. Aimed at improving recognition robustness and fully exploiting the rich information provided by this emerging automotive radar, our approach follows a principled pipeline that comprises (1) dynamic points removal from instant Doppler measurement, (2) spatial-temporal feature embedding on radar point clouds, and (3) retrieved candidates refinement from Radar Cross Section measurement. Extensive experimental results on the public nuScenes dataset demonstrate that existing visual/LiDAR/spinning radar place recognition approaches are less suitable for single-chip automotive radar. In contrast, our purpose-built approach for automotive radar consistently outperforms a variety of baseline methods via a comprehensive set of metrics, providing insights into the efficacy when used in a realistic system.

Abstract (translated)

URL

https://arxiv.org/abs/2109.08652

PDF

https://arxiv.org/pdf/2109.08652.pdf

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