| --- |
| license: apache-2.0 |
| library_name: pytorch |
| tags: |
| - robotics |
| - uav |
| - drone |
| - flow-matching |
| - autonomous-navigation |
| - flightmare |
| --- |
| |
| # FlowPilot Checkpoints |
|
|
| Model checkpoints for **FlowPilot**, a Flow Matching based world-action model for real-time onboard UAV navigation. |
|
|
| The model uses a dual-stream MoT to jointly model video latents and action tokens. Actions are parameterized by a 7th-order Bernstein polynomial with 8 control points (3 fixed by the initial state and 5 predicted by the network), producing 48 waypoints at 30 Hz. |
|
|
| - Code: [flyingbitac/FlowPilot](https://github.com/flyingbitac/FlowPilot) |
|
|
| ## Files |
|
|
| | File | Size | Description | |
| | --- | --- | --- | |
| | `ckpt/phase2/ckpt_final.pt` | 651 MB | Phase-2 checkpoint. The inference state dict is stored under the `model` key; `step`, `optimizer`, and `lr_scheduler` are also included. | |
| | `ckpt/action_stats.pt` | 3.1 KB | Action and state normalization statistics. | |
| | `ckpt/coeff_stats.pt` | 2.7 KB | Bernstein coefficient normalization statistics. | |
|
|
| The Wan2.2 VAE weights are not stored in this repository; download the official file from [Wan-AI/Wan2.2-TI2V-5B](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) as shown below. |
|
|
| ## Usage |
|
|
| Clone the code repository first, then download the checkpoints into its root: |
|
|
| ```bash |
| git clone https://github.com/flyingbitac/FlowPilot.git |
| cd FlowPilot |
| |
| hf download YuDinging/FlowPilot --include "ckpt/*" --local-dir . |
| hf download Wan-AI/Wan2.2-TI2V-5B Wan2.2_VAE.pth --local-dir ckpt |
| ``` |
|
|
| If `hf` is not available, install it with `pip install -U huggingface_hub`. |
|
|
| The `--include "ckpt/*"` filter matters: without it, `hf download` would also write this model card as `README.md` and overwrite the README of the code repository. |
|
|
| The files land under `ckpt/`, the default location expected by `configs/runtime/rviz.py`: |
|
|
| ``` |
| ckpt/ |
| ├── phase2/ckpt_final.pt |
| ├── Wan2.2_VAE.pth |
| ├── action_stats.pt |
| └── coeff_stats.pt |
| ``` |
|
|
| `hf download` also creates a `.cache/huggingface/` directory in the current directory. It only holds download metadata and can be removed afterwards. If you prefer to keep the weights outside the repository, download to another directory with `--local-dir` and symlink its `ckpt/` into the repository instead. |
|
|
|
|
|
|
| Then start the simulation from the code repository: |
|
|
| ```bash |
| python docker/docker.py build |
| python docker/docker.py start |
| ``` |
|
|
| ## Intended Use |
|
|
| These weights are released for research on learning-based UAV navigation, mainly for simulation and onboard inference experiments. They are not certified for safety-critical flight. |
|
|
| ## License |
|
|
| The checkpoints are released under the Apache License 2.0. |
|
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| `ckpt/Wan2.2_VAE.pth` is downloaded from the official [Wan2.2 model repository](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) (Alibaba Wan Team) and is also licensed under Apache-2.0. |
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|
