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DARPA Subterranean Challenge: Finals

Datasets recorded onboard an autonomous UAV system (described in [1, 2]) deployed within the environment of the DARPA Subterranean Challenge Finals (post-event testing). Contains mid-range flights in extremely narrow subterranean environments, with perceptual degradation from whirling dust, no dynamic obstacles, one mine-cave-mine loop, average speed ~0.5 m/s.

The rosbags contain unsynchronized LiDAR points and image streams of two cameras. The groundtruth trajectory was estimated (code) during post-processing: registration of on-board data onto the map of the environment using ICP set with high-precision parameters.

Datasets

Dataset UAV name Length (m, s) Environment Loop Dust noise Autonomy GoPro
uav21_2 uav21 306, 757 metro no no link N/A
uav21_3 uav21 23, 58 cave no no link N/A
uav21_4 uav21 196, 432 mine no yes link N/A
uav21_5 uav21 377, 914 metro no no link N/A
uav21_6 uav21 164, 432 mine and cave yes yes link link
uav22_1 uav22 131, 332 mine no yes link N/A
uav22_2 uav22 347, 347 mine no yes link link
uav22_3 uav22 266, 644 metro no no link N/A
uav24_1 uav24 162, 475 urban storeroom no no link link

Sensors

  • OS0-128 LiDAR (128 rows, 90 deg vFoV) topics:
    • raw points: /UAV_NAME/os_cloud_nodelet/points of type sensor_msgs/PointCloud2
      • to filter out the UAV frame, use points with minimal distance of 0.5 m from the sensor origin
    • processed points: /UAV_NAME/os_cloud_nodelet/points_processed of type sensor_msgs/PointCloud2
      • 32 rows (every 4-th row of raw data, evenly spaced), filtered UAV frame, filtered dust
  • Basler RGB cameras:
    • resolution: 600 x 800 px
    • two cameras [basler_left, basler_right]
    • camera_info: /UAV_NAME/basler_X/image_raw/camera_info of type sensor_msgs/CameraInfo
    • image: /UAV_NAME/basler_X/image_raw/compressed of type sensor_msgs/CompressedImage

Frames

  • baselink: UAV_NAME/fcu
  • points: UAV_NAME/os_lidar
  • camera basler_X [basler_left, basler_right]:
    • optical frame: UAV_NAME/basler_X_optical
    • ROS frame: UAV_NAME/basler_X
UAV_NAME/fcu
└───> UAV_NAME/os_sensor
      └───> UAV_NAME/os_lidar
      └───> UAV_NAME/basler_X_optical
      └───> UAV_NAME/basler_X

Folder structure

subt_finals
│   download.sh
│   subt_finals.pcd
│
└───DATASET
│       trajectory_groundtruth.txt
│       rosbag.bag
│       fcu_in_map.mat
└───...
  • Script to download large data: download.sh
    • ground truth map of the environment: subt_finals.pcd
    • datasets: rosbag.bag
  • Ground truth trajectory: trajectory_groundtruth.txt
    • in local origin (use fcu_in_map.mat to transform to the map frame): zero-pose initialization
    • format: timestamp x y z qx qy qz qw
  • General mission information: mission_data.txt
  • Initial transformation map->UAV_NAME/fcu: fcu_in_map.mat
    • 4x4 transformation matrix

References

  • [1] Petracek, P.; Kratky, V.; Petrlik, M.; Baca, T.; Kratochvil, R.; Saska, M. Large-Scale Exploration of Cave Environments by Unmanned Aerial Vehicles, IEEE Robotics and Automation Letters 2021, 6, 7596–7603.
  • [2] V. Kratky, P. Petracek, T. Baca and M. Saska, An autonomous unmanned aerial vehicle system for fast exploration of large complex indoor environments, Journal of field robotics, May 2021.