Robotics: Science and Systems XVII

GROUNDED: The Localizing Ground Penetrating Radar Evaluation Dataset

Teddy Ort, Igor Gilitschenski, Daniela Rus

Abstract:

Mapping and localization using surface features is prone to failure due to environment changes such as inclement weather. Recently; Localizing Ground Penetrating Radar (LGPR) has been proposed as an alternative means of localizing using underground features that are stable over time and less affected by surface conditions. However; due to the lack of commercially available LGPR sensors; the wider research community has been largely unable to replicate this work or build new and innovative solutions. We present GROUNDED an open dataset of LGPR scans collected in a variety of environments and weather conditions. By labeling this data with ground truth localization from an RTK-GPS / Inertial Navigation System; and carefully calibrating and time synchronizing the radar scans with ground truth positions; camera imagery; and Lidar data; we enable researchers to build novel localization solutions that are resilient to changing surface conditions. We include 108 individual runs totalling 450 km of driving with LGPR; GPS; Odometry; Camera; and Lidar measurements. We also present two new evaluation benchmarks for 1) Localizing in Weather and 2) Multi-lane Mapping; to enable comparisons of future work supported by the dataset. The dataset can be accessed at http://lgprdata.com.

Download:

Bibtex:

  
@INPROCEEDINGS{Ort-RSS-21, 
    AUTHOR    = {Teddy Ort AND Igor Gilitschenski AND Daniela Rus}, 
    TITLE     = {{GROUNDED: The Localizing Ground Penetrating Radar Evaluation Dataset}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2021}, 
    ADDRESS   = {Virtual}, 
    MONTH     = {July}, 
    DOI       = {10.15607/RSS.2021.XVII.080} 
}