Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?
Burnett, Keenan, Wu, Yuchen, Yoon, David J., Schoellig, Angela P., Barfoot, Timothy D.
–arXiv.org Artificial Intelligence
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: https://github.com/utiasASRL/vtr3
arXiv.org Artificial Intelligence
Jun-8-2023
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