ColoRadar: The direct 3D millimeter wave radar dataset. (April 2022)

• Record Type: Journal Article
• Authors: Kramer, Andrew; Harlow, Kyle; Williams, Christopher; Heckman, Christoffer
• Is Part Of: International journal of robotics research. Volume 41:Number 4(2022)
• Page Start: 351
• Page End: 360
• Publication Date: 2022-04
• Subjects: Dataset -- radar -- field robotics -- SLAM -- odometry -- mapping; Robots -- Periodicals; Robots, Industrial -- Periodicals; 629.89205
• DOI: 10.1177/02783649211068535
• Languages: English
• ISSNs: 0278-3649

Abstract

This work presents two different forms of dense, high-resolution radar data from two frequency modulated continuous wave radar sensors, along sparse radar pointclouds produced by one of the radar sensors. In addition, all datasets include 3D lidar and inertial measurements, and a lidar-based simultaneous localization and mapping pose estimation. Over 2 h of 6D pose data was generated across 52 datasets collected in highly diverse 3D environments including lab spaces, outside and inside large buildings, urban walkways, and a mine. One dataset, from the ASPEN Lab, also includes precision groundtruth generated from a motion capture system. Intrinsic radar calibration and measured extrinsic sensor position calibrations are also provided along with python based development tools to interact with the various datasets. This data is designed to assist with generating radar based localization algorithms and calibrations between radar and other sensors.