Astral eco — drone navigation policies
Trained RL navigation policies for the astral-us/eco drone
platform (quadcopter, rover, fixed-wing). Each policy takes a 56-dim forward-depth state and
outputs a 4-dim [vx, vy, vz, yaw_rate] action; see eco/drone/training/contract.py /
fw_contract.py for the exact state layout.
These are optional. The platform's core, benchmarked result — the L5 zero-intervention
fleet controller (eco/drone/common/L5.md) — is classical potential-field control with no
model weights at all. These .onnx files back a separate, secondary learned-policy path
(LearnedPlanner in reactive_planner.py) used mainly for the Isaac Sim demo renders; in the
team's own testing it underperforms the classical controller on the L5 benchmark.
Files
| File | Vehicle | Kinematics | Notes |
|---|---|---|---|
policy_v26rnn_dr.onnx |
Quadcopter | Holonomic 3D | Domain-randomized, RNN policy |
policy_rover_v2.onnx + policy_rover_v2.onnx.data |
Rover | Unicycle 2D | External-data ONNX (needs the .data file alongside it) |
policy_fw.onnx |
Fixed-wing | Coordinated-turn 3D (Dubins-airplane) | Early checkpoint (800 PPO iters from scratch, ~47% success at full domain randomization) |
Usage
Download into eco/drone/models/ (the filenames already match what vehicle_class.py expects
as each class's default policy_onnx):
pip install huggingface_hub
python -c "
from huggingface_hub import hf_hub_download
for f in ['policy_v26rnn_dr.onnx', 'policy_rover_v2.onnx', 'policy_rover_v2.onnx.data', 'policy_fw.onnx']:
hf_hub_download(repo_id='astralhf/eco-drone-policies', filename=f, local_dir='eco/drone/models')
"
Or with the CLI:
huggingface-cli download astralhf/eco-drone-policies --local-dir eco/drone/models
Training your own
See eco/drone/training/justfile — train / train-ma / train-fw recipes (PPO from scratch
or with BC warm-start, run on a CUDA GPU), and pull / pull-ma / pull-fw to fetch the
result. The fixed-wing policy here is an early checkpoint; retraining for longer or with tighter
domain randomization is expected to improve on it.