HUTACE-I5x64x64-B8x8-T65-0.83M
HUTACE is the Hybrid U-Net–Transformer Actor–Critic for Exploration. It selects local waypoints for energy-constrained coverage exploration from a partially observed 2.5D terrain.
The checkpoint has 833,795 parameters. It uses a 5×64×64 state, an 8×8 U-Net bottleneck, 64 spatial Transformer tokens plus one summary token (T65), two Transformer layers, and four attention heads.
- Interactive 3D demo: HUTACE 3D Explorer
- Frozen benchmark package: HUTACE Mapzen Benchmark
Input and output
Input is float32[5,64,64] in this order:
- observed relative elevation,
(elevation - start_elevation) / 200, clipped to[-3,3] - observed-cell mask
- current-position one-hot map
- visit count normalized as
clip(count/3, 0, 1) - remaining-fuel ratio.
The model returns 4,096 waypoint logits and one critic value.
Quick use
from huggingface_hub import snapshot_download
import sys
repo = snapshot_download(
"Moon-Young-Choi/HUTACE-I5x64x64-B8x8-T65-0.83M",
revision="74e3bf02f3fb9636e2c418ac42f0251b2e25acfe",
)
sys.path.insert(0, repo)
from inference import load_model, select_action
model = load_model(repo)
action = select_action(state, action_mask, model=model)
state must be NumPy-compatible with shape [5,64,64]; action_mask must be Boolean-compatible with shape [4096]. For a compatible terrain NPZ containing elevation_m[64,64], use:
python run_exploration.py --terrain terrain.npz --seed 523 --output result.json
Frozen Mapzen test results
| Method | Final coverage | Coverage–energy AUC | Coverage at 320 | Energy to 50% (censored; lower is better) |
|---|---|---|---|---|
| HUTACE | 0.7712 | 0.5213 | 0.5884 | 302.12 |
| Plain U-Net PPO | 0.6679 | 0.4511 | 0.5090 | 369.77 |
| CNN PPO | 0.5454 | 0.4062 | 0.4725 | 408.95 |
| Nearest frontier | 0.6114 | 0.3557 | 0.3636 | 494.37 |
| Random local waypoint | 0.4287 | 0.2684 | 0.2830 | 590.17 |
| Expected gain / estimated energy | 0.1405 | 0.1305 | 0.1402 | 612.55 |
HUTACE outperformed CNN PPO, Plain U-Net PPO, and all three listed partial-observation heuristics on these frozen-test means.
Terrain provenance
Training, validation, and test use Mapzen Terrain Tiles on AWS Open Data. Mapzen combines multiple regional source DEMs; it is not a single NASA or Copernicus dataset. Zoom-13 tiles are resampled onto a local-UTM 30 m simulator grid, which is not a universal native-resolution claim. Full source attribution is in docs/mapzen_attribution.md.