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license: apache-2.0
task_categories:
- robotics
- reinforcement-learning
tags:
- aerial-navigation
- world-model
- embodied-ai
- uav
---
# ANWM-Dataset
Training / evaluation trajectories for **ANWM** (Aerial Navigation World Model),
released with the paper
[Aerial World Model for Long-horizon Visual Generation and Navigation in 3D Space](https://arxiv.org/abs/2512.21887).
- **Code**: [https://github.com/EmbodiedCity/ANWM.code](https://github.com/EmbodiedCity/ANWM.code)
- **Model**: [EmbodiedCity/ANWM](https://huggingface.co/EmbodiedCity/ANWM)
## Contents
Sharded tar archives of AirVLN-16 style trajectories (`airvln_16-*.tar`).
Each archive preserves the original folder layout (`{ID}_processed/...` with
images and `traj_data.pkl`).
## Quick start
```bash
git clone https://github.com/EmbodiedCity/ANWM.code.git
cd ANWM.code
huggingface-cli download EmbodiedCity/ANWM-Dataset --repo-type dataset \
--local-dir data/airvln_16_shards
mkdir -p data/airvln_16
for f in data/airvln_16_shards/airvln_16-*.tar; do
tar -xf "$f" -C data/airvln_16
done
```
After extract, trajectory directories are directly under `data/airvln_16/`.
Also download the released checkpoint:
```bash
huggingface-cli download EmbodiedCity/ANWM 0200000.pth.tar \
--local-dir logs/anwm_cdit_airvln/checkpoints
```
See the code repository README for installation, inference, and evaluation.
## Related
- Code: https://github.com/EmbodiedCity/ANWM.code
- Model: https://huggingface.co/EmbodiedCity/ANWM
- Dataset: https://huggingface.co/datasets/EmbodiedCity/ANWM-Dataset
- Paper: https://arxiv.org/abs/2512.21887
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