[2203.10174] Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?
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Computer Science > Robotics

arXiv:2203.10174 (cs)
[Submitted on 18 Mar 2022 (v1), last revised 8 Jun 2023 (this version, v3)]

Title:Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?

Authors:Keenan Burnett, Yuchen Wu, David J. Yoon, Angela P. Schoellig, Timothy D. Barfoot
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Abstract:We present an extensive comparison between three topometric localization systems: radar-only, lidar-only, and a cross-modal radar-to-lidar system across varying seasonal and weather conditions using the Boreas dataset. Contrary to our expectations, our experiments showed that our lidar-only pipeline achieved the best localization accuracy even during a snowstorm. Our results seem to suggest that the sensitivity of lidar localization to moderate precipitation has been exaggerated in prior works. However, our radar-only pipeline was able to achieve competitive accuracy with a much smaller map. Furthermore, radar localization and radar sensors still have room to improve and may yet prove valuable in extreme weather or as a redundant backup system. Code for this project can be found at: this https URL
Comments: Version 3: Accepted to RA-L, presented at IROS 2022. Localization results updated due to improved ground truth and calibration. Also switched Huber Loss for Cauchy Loss for the radar-based approaches
Subjects: Robotics (cs.RO)
Cite as: arXiv:2203.10174 [cs.RO]
  (or arXiv:2203.10174v3 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2203.10174

Submission history

From: Keenan Burnett [view email]
[v1] Fri, 18 Mar 2022 21:58:34 UTC (8,707 KB)
[v2] Mon, 23 May 2022 20:31:30 UTC (13,001 KB)
[v3] Thu, 8 Jun 2023 15:32:50 UTC (7,555 KB)
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