README.md

metadata

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.

• Code: https://github.com/EmbodiedCity/ANWM.code
• Model: 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

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:

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