File size: 2,179 Bytes
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license: other
task_categories:
- robotics
- other
language:
- en
tags:
- embodied-ai
- tracking
- dagger
- habitat
pretty_name: OpenTrackVLA DAgger Recovery Dataset
---
# OpenTrackVLA DAgger Recovery Dataset
Training-only DAgger recovery data generated in Habitat for OpenTrackVLA target
tracking. This release contains V6-policy failure recovery data for AT, DT, and
STT, using seeds 101 and 102.
The uploaded payload contains only the final training-ready datasets:
- JSONL trajectory labels;
- referenced RGB frames;
- precomputed DINOv3 + SigLIP fine/coarse visual-token caches;
- conversion, filtering, and integrity metadata.
Source rollouts, raw recovery videos, evaluation-scene data, model checkpoints,
and EVT-Bench results are not included.
## Layout
```text
packed/v6_failures/train/<task>/seed_<seed>/
jsonl.tar.zst.part-0000...
frames.tar.zst.part-0000...
vision_cache.tar.zst.part-0000...
metadata/v6_failures/train/<task>/seed_<seed>/
dataset_stats.json
dataset_inspection.json
dagger_selection_plan.json
referenced_frames.txt
*.manifest.json
```
Each component is a Zstandard-compressed tar stream split into numbered parts.
Reconstruct one component with:
```bash
cat <component>.tar.zst.part-* | tar --zstd -xf - -C /path/to/dataset
```
Every component manifest records the ordered part names, byte sizes, and SHA256
checksums. Verify all parts before extraction.
## Data policy
This dataset is derived from simulated Habitat/HM3D tracking episodes. Users are
responsible for complying with the licenses and terms of the upstream scene,
avatar, simulator, and model assets. The `other` license marker is intentional:
it does not replace those upstream terms.
## Generation
- Split: training scenes and training avatars only
- Tasks: AT, DT, STT
- Seeds: 101, 102
- History: 31 frames
- Prediction horizon: 8 waypoints
- DAgger target fraction: 0.25
- Failure window: 12 steps
- Intervention pre/post windows: 12/8 steps
- Maximum retained samples per episode: 26
Deterministic Habitat native-process crashes are explicitly audited and excluded;
they are never converted into synthetic success/failure labels.
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