Instructions to use nepyope/g1_depth_dodge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use nepyope/g1_depth_dodge with LeRobot:
- Notebooks
- Google Colab
- Kaggle
G1 depth dodgeball on frozen SONIC (ONNX deploy)
Frozen SONIC whole-body controller + seven rank-16 LoRAs on the decoder, conditioned on a
128-d percept from a head depth camera (Theia-Tiny tokens + temporal adapter). PPO, iteration 4000.
Consumed by lerobot's DepthDodgeController for the Unitree G1.
| file | inputs | outputs |
|---|---|---|
theia_image.onnx |
image uint8 [B,224,224] (depth mapped 255 near .. 1 far, 0 invalid) |
tokens [B,197,192] fp32 |
perception.onnx |
depth_tokens fp32 [1,16,197,192] (16-frame ring at 25 Hz, fp16-rounded) |
percept [1,128] |
actor.onnx |
tokenizer[1,640], policy[1,930], conditioning[1,768] = concat(tokenizer, percept) |
actions[1,29] SONIC-normalized PD residuals, MuJoCo joint order |
Camera contract: 64x96 optical-Z depth in metres, 45 deg vertical FOV, 0 deg pitch, valid 0.2-6 m, 25 Hz.
See manifest.json for the full training config.
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