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Manipulation datasetOpen

TartanDrive 2.0

TartanDrive 2.0 is an expanded large-scale off-road driving dataset from CMU's AirLab, collected on a Yamaha Viking All-Terrain Vehicle (ATV named 'Vicky') over 255+ acres of diverse terrain in Western Pennsylvania (narrow paths, dense foliage, rocky areas, dirt paths, steep hills). It comprises roughly 7 hours of data at speeds up to 15 m/s. Building on TartanDrive 1.0, version 2.0 adds three LiDAR sensors: two Velodyne VLP-32 units (front-roof mounted, one tilted downward) and one Livox Mid-70 (under the camera), all at 10 Hz. The camera system is a Carnegie Robotics MultiSense S21 providing stereo greyscale images plus a left RGB image at 10 Hz. Inertial/positioning comes from a NovAtel PROPAK-V3-RT2i GNSS (IMU at 100 Hz, GPS-fused pose at 50 Hz) and the MultiSense IMU at 400 Hz. Proprioceptive data (Racepak G2X Pro logger plus joystick/pedals) includes per-wheel RPM, rear suspension shock travel, steering commands and angle, and accelerator/brake pedal positions. Post-processed products include TartanVO and Super Odometry estimates, registered point clouds, predicted point clouds, heightmaps, RGB bird's-eye-view maps, IMU-derived roughness cost, and 200x200m BEV LiDAR feature maps at 0.5m resolution (min/max/mean height, roughness, SVD features, ground height/slope). Rich per-sequence metadata (driver ID, vehicle, passenger count, date/time, weather, lighting, course ID, top/average speed, duration) plus timestamped event annotations and 1-5 driving-quality scores are included. Data is distributed both as original rosbags and in a KITTI-like time-synced sequence format, with scripts to regenerate data at custom sample frequency, map size and resolution. A GUI tool (scripts/tartandrive_gui.py) lets users browse runs and select which modalities to download to save storage; a point-cloud scan of the ATV is downloadable separately. Released alongside the ICRA 2024 paper (arXiv:2402.01913).

Scale
7 hours
Formats
custom · rosbag
License
MIT
Published
2024-02-02

Decision summary

Best for

manual_operation

Main blocker

Metadata requires review against the official source before publication.

Next check

Read the dataset manifest and feature schema.

Catalog assessment

Selection evidence

73/100

Provisional · confidence 48 · 4/6 evaluated

Access and governance

Access and license are declared by the source.

usefulfit 75 · confidence 85

Schema and signal coverage

No machine-readable schema has been verified yet.

unknownnot scored · confidence 15

Policy training readiness

Observation and action/state signals are declared; alignment quality still depends on sample verification.

usefulfit 70 · confidence 55
View 3 more dimensions

World-model readiness

Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.

usefulfit 82 · confidence 50

Failure and recovery readiness

No verified failure/recovery annotation evidence is available yet.

unknownnot scored · confidence 15

Download and processing readiness

Scale is declared; transfer and processing estimates are not measured.

usefulfit 65 · confidence 65
Review unresolved evidence and next checks

Signal gaps

  • Feedback / correction / failure. Not enough evidence is available to classify this signal.

Next checks

  • Read the dataset manifest and feature schema.
  • Run a bounded sample audit before assigning Strong readiness.

Record specifics

Dataset facts

Source
CMU AirLab
Evidence
secondary claim
Formats
custom · rosbag
hours
7
Read paper

Metadata coverage

Loop signals

6/7 present or partial

Feedback / correction / failure

No decision-grade evidence captured yet.

unknown
View 6 more signal categories
Observation / ego video

depth · video · TartanDrive 2.0 is an expanded large-scale off-road driving dataset from CMU's AirLab, collected on a Yamaha Viking All-Terrain Vehicle (ATV named 'Vicky') over 255+ acres of diverse terrain in Western Pennsylvania (narrow paths, dense foliage, rocky areas, dirt paths, steep hills). It comprises roughly 7 hours of data at speeds up to 15 m/s. Building on TartanDrive 1.0, version 2.0 adds three LiDAR sensors: two Velodyne VLP-32 units (front-roof mounted, one tilted downward) and one Livox Mid-70 (under the camera), all at 10 Hz. The camera system is a Carnegie Robotics MultiSense S21 providing stereo greyscale images plus a left RGB image at 10 Hz. Inertial/positioning comes from a NovAtel PROPAK-V3-RT2i GNSS (IMU at 100 Hz, GPS-fused pose at 50 Hz) and the MultiSense IMU at 400 Hz. Proprioceptive data (Racepak G2X Pro logger plus joystick/pedals) includes per-wheel RPM, rear suspension shock travel, steering commands and angle, and accelerator/brake pedal positions. Post-processed products include TartanVO and Super Odometry estimates, registered point clouds, predicted point clouds, heightmaps, RGB bird's-eye-view maps, IMU-derived roughness cost, and 200x200m BEV LiDAR feature maps at 0.5m resolution (min/max/mean height, roughness, SVD features, ground height/slope). Rich per-sequence metadata (driver ID, vehicle, passenger count, date/time, weather, lighting, course ID, top/average speed, duration) plus timestamped event annotations and 1-5 driving-quality scores are included. Data is distributed both as original rosbags and in a KITTI-like time-synced sequence format, with scripts to regenerate data at custom sample frequency, map size and resolution. A GUI tool (scripts/tartandrive_gui.py) lets users browse runs and select which modalities to download to save storage; a point-cloud scan of the ATV is downloadable separately. Released alongside the ICRA 2024 paper (arXiv:2402.01913).

present
Action / hand pose / robot state

TartanDrive 2.0 is an expanded large-scale off-road driving dataset from CMU's AirLab, collected on a Yamaha Viking All-Terrain Vehicle (ATV named 'Vicky') over 255+ acres of diverse terrain in Western Pennsylvania (narrow paths, dense foliage, rocky areas, dirt paths, steep hills). It comprises roughly 7 hours of data at speeds up to 15 m/s. Building on TartanDrive 1.0, version 2.0 adds three LiDAR sensors: two Velodyne VLP-32 units (front-roof mounted, one tilted downward) and one Livox Mid-70 (under the camera), all at 10 Hz. The camera system is a Carnegie Robotics MultiSense S21 providing stereo greyscale images plus a left RGB image at 10 Hz. Inertial/positioning comes from a NovAtel PROPAK-V3-RT2i GNSS (IMU at 100 Hz, GPS-fused pose at 50 Hz) and the MultiSense IMU at 400 Hz. Proprioceptive data (Racepak G2X Pro logger plus joystick/pedals) includes per-wheel RPM, rear suspension shock travel, steering commands and angle, and accelerator/brake pedal positions. Post-processed products include TartanVO and Super Odometry estimates, registered point clouds, predicted point clouds, heightmaps, RGB bird's-eye-view maps, IMU-derived roughness cost, and 200x200m BEV LiDAR feature maps at 0.5m resolution (min/max/mean height, roughness, SVD features, ground height/slope). Rich per-sequence metadata (driver ID, vehicle, passenger count, date/time, weather, lighting, course ID, top/average speed, duration) plus timestamped event annotations and 1-5 driving-quality scores are included. Data is distributed both as original rosbags and in a KITTI-like time-synced sequence format, with scripts to regenerate data at custom sample frequency, map size and resolution. A GUI tool (scripts/tartandrive_gui.py) lets users browse runs and select which modalities to download to save storage; a point-cloud scan of the ATV is downloadable separately. Released alongside the ICRA 2024 paper (arXiv:2402.01913).

partial
Gaze / attention

TartanDrive 2.0 is an expanded large-scale off-road driving dataset from CMU's AirLab, collected on a Yamaha Viking All-Terrain Vehicle (ATV named 'Vicky') over 255+ acres of diverse terrain in Western Pennsylvania (narrow paths, dense foliage, rocky areas, dirt paths, steep hills). It comprises roughly 7 hours of data at speeds up to 15 m/s. Building on TartanDrive 1.0, version 2.0 adds three LiDAR sensors: two Velodyne VLP-32 units (front-roof mounted, one tilted downward) and one Livox Mid-70 (under the camera), all at 10 Hz. The camera system is a Carnegie Robotics MultiSense S21 providing stereo greyscale images plus a left RGB image at 10 Hz. Inertial/positioning comes from a NovAtel PROPAK-V3-RT2i GNSS (IMU at 100 Hz, GPS-fused pose at 50 Hz) and the MultiSense IMU at 400 Hz. Proprioceptive data (Racepak G2X Pro logger plus joystick/pedals) includes per-wheel RPM, rear suspension shock travel, steering commands and angle, and accelerator/brake pedal positions. Post-processed products include TartanVO and Super Odometry estimates, registered point clouds, predicted point clouds, heightmaps, RGB bird's-eye-view maps, IMU-derived roughness cost, and 200x200m BEV LiDAR feature maps at 0.5m resolution (min/max/mean height, roughness, SVD features, ground height/slope). Rich per-sequence metadata (driver ID, vehicle, passenger count, date/time, weather, lighting, course ID, top/average speed, duration) plus timestamped event annotations and 1-5 driving-quality scores are included. Data is distributed both as original rosbags and in a KITTI-like time-synced sequence format, with scripts to regenerate data at custom sample frequency, map size and resolution. A GUI tool (scripts/tartandrive_gui.py) lets users browse runs and select which modalities to download to save storage; a point-cloud scan of the ATV is downloadable separately. Released alongside the ICRA 2024 paper (arXiv:2402.01913).

partial
Language intent / task phase

TartanDrive 2.0 is an expanded large-scale off-road driving dataset from CMU's AirLab, collected on a Yamaha Viking All-Terrain Vehicle (ATV named 'Vicky') over 255+ acres of diverse terrain in Western Pennsylvania (narrow paths, dense foliage, rocky areas, dirt paths, steep hills). It comprises roughly 7 hours of data at speeds up to 15 m/s. Building on TartanDrive 1.0, version 2.0 adds three LiDAR sensors: two Velodyne VLP-32 units (front-roof mounted, one tilted downward) and one Livox Mid-70 (under the camera), all at 10 Hz. The camera system is a Carnegie Robotics MultiSense S21 providing stereo greyscale images plus a left RGB image at 10 Hz. Inertial/positioning comes from a NovAtel PROPAK-V3-RT2i GNSS (IMU at 100 Hz, GPS-fused pose at 50 Hz) and the MultiSense IMU at 400 Hz. Proprioceptive data (Racepak G2X Pro logger plus joystick/pedals) includes per-wheel RPM, rear suspension shock travel, steering commands and angle, and accelerator/brake pedal positions. Post-processed products include TartanVO and Super Odometry estimates, registered point clouds, predicted point clouds, heightmaps, RGB bird's-eye-view maps, IMU-derived roughness cost, and 200x200m BEV LiDAR feature maps at 0.5m resolution (min/max/mean height, roughness, SVD features, ground height/slope). Rich per-sequence metadata (driver ID, vehicle, passenger count, date/time, weather, lighting, course ID, top/average speed, duration) plus timestamped event annotations and 1-5 driving-quality scores are included. Data is distributed both as original rosbags and in a KITTI-like time-synced sequence format, with scripts to regenerate data at custom sample frequency, map size and resolution. A GUI tool (scripts/tartandrive_gui.py) lets users browse runs and select which modalities to download to save storage; a point-cloud scan of the ATV is downloadable separately. Released alongside the ICRA 2024 paper (arXiv:2402.01913).

partial
Sim-real pairing

depth

present
License / format / access

Open · MIT · custom · rosbag

partial
Evidence details and provenance

Official signal claims

DepthPoint_cloudProprioceptionVideo

Schema and annotations

No machine-readable schema facts are captured.

Sample verification

Pending. Metadata does not prove sample coverage, alignment, or file integrity.

curated official source

Integration notes

  • Metadata requires review against the official source before publication.

Catalog links

Related records