U2UData+
U2UData+ (published under the name U2UData-2) is a large-scale swarm-UAV dataset for Embodied Long-Horizon tasks, collected entirely in the U2USim UE5.2/AirSim simulator on terrain mapped from Yunnan Province.
Source notes
U2UData+ (published under the name U2UData-2) is a large-scale swarm-UAV dataset for Embodied Long-Horizon tasks, collected entirely in the U2USim UE5.2/AirSim simulator on terrain mapped from Yunnan Province. Fifteen UAVs fly in autonomous formation mode executing a wildlife-conservation task across 12 weather and terrain scenes, producing 720 traces of 600 s each — 12.96M RGB frames, 12.96M depth frames, 4.32M LiDAR sweeps, plus brightness, temperature, humidity, smoke and airflow readings. It ships with an online data-collection and closed-loop verification platform, 3D bounding boxes for 15 object classes, and a collaborative-tracking benchmark over 9 methods. Accepted at AAAI 2026; supersedes the smaller U2UData (ACM MM 2024, 3 UAVs / 8.75 h).
Partial public release: only 1 of the 12 scenes (~62 GB) is on HuggingFace. The full 3.62 TB requires emailing the authors for a Baidu Cloud link. The size shown here is the full dataset.
- Scale
- 120 hours
- Formats
- custom
- License
- Apache-2.0
- Published
- 2025-08-25
Decision summary
scripted
Metadata requires review against the official source before publication.
Read the dataset manifest and feature schema.
Release history
Source-backed release timing for this canonical dataset record.
- Release evidence
Dataset series published
Release timing is recorded from official dataset metadata.
Selection readiness
6 evidence dimensions for deciding whether this dataset is ready to inspect, compare, or adopt. This is not a model benchmark.
Catalog evidence · not task performance
How scores work73/100
Provisional
4/6 dimensions scored · 48% confidence
Read the evidence behind all 6 dimensions
Access and governance
Access and license are declared by the source.
Schema and signal coverage
No machine-readable schema has been verified yet.
Policy training readiness
Observation and action/state signals are declared; alignment quality still depends on sample verification.
World-model readiness
Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.
Failure and recovery readiness
No verified failure/recovery annotation evidence is available yet.
Download and processing readiness
Scale is declared; transfer and processing estimates are not measured.
Review unresolved evidence and next checks
Signal gaps
- Action / hand pose / robot state. Not enough evidence is available to classify this signal.
- Gaze / attention. 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.
Engineering checks (OBRS) behind this record
Needs Audit
OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.
- A passing real-hardware test report is required.
- A passing ingestion/pipeline test report is required.
- A passing privacy and provenance review is required.
Dataset facts
- Source
- Tsinghua University — THU-EAI Lab
- Evidence
- secondary claim
- Formats
- custom
- episodes
- 720
- hours
- 120
- tasks
- 1
Loop signals
5/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 5 more signal categories
depth · video · U2UData+ (published under the name U2UData-2) is a large-scale swarm-UAV dataset for Embodied Long-Horizon tasks, collected entirely in the U2USim UE5.2/AirSim simulator on terrain mapped from Yunnan Province. Fifteen UAVs fly in autonomous formation mode executing a wildlife-conservation task across 12 weather and terrain scenes, producing 720 traces of 600 s each — 12.96M RGB frames, 12.96M depth frames, 4.32M LiDAR sweeps, plus brightness, temperature, humidity, smoke and airflow readings. It ships with an online data-collection and closed-loop verification platform, 3D bounding boxes for 15 object classes, and a collaborative-tracking benchmark over 9 methods. Accepted at AAAI 2026; supersedes the smaller U2UData (ACM MM 2024, 3 UAVs / 8.75 h). *Partial public release: only 1 of the 12 scenes (~62 GB) is on HuggingFace. The full 3.62 TB requires emailing the authors for a Baidu Cloud link. The size shown here is the full dataset.*
presentU2UData+ (published under the name U2UData-2) is a large-scale swarm-UAV dataset for Embodied Long-Horizon tasks, collected entirely in the U2USim UE5.2/AirSim simulator on terrain mapped from Yunnan Province. Fifteen UAVs fly in autonomous formation mode executing a wildlife-conservation task across 12 weather and terrain scenes, producing 720 traces of 600 s each — 12.96M RGB frames, 12.96M depth frames, 4.32M LiDAR sweeps, plus brightness, temperature, humidity, smoke and airflow readings. It ships with an online data-collection and closed-loop verification platform, 3D bounding boxes for 15 object classes, and a collaborative-tracking benchmark over 9 methods. Accepted at AAAI 2026; supersedes the smaller U2UData (ACM MM 2024, 3 UAVs / 8.75 h). *Partial public release: only 1 of the 12 scenes (~62 GB) is on HuggingFace. The full 3.62 TB requires emailing the authors for a Baidu Cloud link. The size shown here is the full dataset.*
partialU2UData+ (published under the name U2UData-2) is a large-scale swarm-UAV dataset for Embodied Long-Horizon tasks, collected entirely in the U2USim UE5.2/AirSim simulator on terrain mapped from Yunnan Province. Fifteen UAVs fly in autonomous formation mode executing a wildlife-conservation task across 12 weather and terrain scenes, producing 720 traces of 600 s each — 12.96M RGB frames, 12.96M depth frames, 4.32M LiDAR sweeps, plus brightness, temperature, humidity, smoke and airflow readings. It ships with an online data-collection and closed-loop verification platform, 3D bounding boxes for 15 object classes, and a collaborative-tracking benchmark over 9 methods. Accepted at AAAI 2026; supersedes the smaller U2UData (ACM MM 2024, 3 UAVs / 8.75 h). *Partial public release: only 1 of the 12 scenes (~62 GB) is on HuggingFace. The full 3.62 TB requires emailing the authors for a Baidu Cloud link. The size shown here is the full dataset.*
partialdepth · simulation · U2UData+ (published under the name U2UData-2) is a large-scale swarm-UAV dataset for Embodied Long-Horizon tasks, collected entirely in the U2USim UE5.2/AirSim simulator on terrain mapped from Yunnan Province. Fifteen UAVs fly in autonomous formation mode executing a wildlife-conservation task across 12 weather and terrain scenes, producing 720 traces of 600 s each — 12.96M RGB frames, 12.96M depth frames, 4.32M LiDAR sweeps, plus brightness, temperature, humidity, smoke and airflow readings. It ships with an online data-collection and closed-loop verification platform, 3D bounding boxes for 15 object classes, and a collaborative-tracking benchmark over 9 methods. Accepted at AAAI 2026; supersedes the smaller U2UData (ACM MM 2024, 3 UAVs / 8.75 h). *Partial public release: only 1 of the 12 scenes (~62 GB) is on HuggingFace. The full 3.62 TB requires emailing the authors for a Baidu Cloud link. The size shown here is the full dataset.*
presentOpen · Apache-2.0 · custom
partialEvidence details and provenance
Official signal claims
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.