diasAiMaster Claude Opus 4.6 (1M context) commited on
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Update README with deploy.yaml instructions and build steps

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Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

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  1. README.md +11 -1
README.md CHANGED
@@ -43,6 +43,7 @@ RL locomotion policy for the [Unitree Go2](https://www.unitree.com/go2/) quadrup
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  | `policy.onnx` + `policy.onnx.data` | ONNX model for deployment (go2_ctrl) |
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  | `model_500.pt` | Final PyTorch checkpoint (best for fine-tuning) |
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  | `model_0.pt` ... `model_400.pt` | Intermediate checkpoints every 100 steps |
 
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  | `params/env.yaml` | Environment configuration |
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  | `params/agent.yaml` | Agent/PPO configuration |
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  | `events.out.tfevents.*` | TensorBoard training logs |
@@ -52,15 +53,24 @@ RL locomotion policy for the [Unitree Go2](https://www.unitree.com/go2/) quadrup
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  ### Deploy in MuJoCo simulator
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  ```bash
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- # Copy ONNX model
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  cp policy.onnx policy.onnx.data \
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  unitree_rl_mjlab/deploy/robots/go2/config/policy/velocity/v0/exported/
 
 
 
 
 
 
 
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  # Run simulator + controller
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  cd unitree_mujoco/simulate/build && ./unitree_mujoco
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  cd unitree_rl_mjlab/deploy/robots/go2/build && ./go2_ctrl --network=lo
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  ```
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  ### Fine-tune on rough terrain
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  ```bash
 
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  | `policy.onnx` + `policy.onnx.data` | ONNX model for deployment (go2_ctrl) |
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  | `model_500.pt` | Final PyTorch checkpoint (best for fine-tuning) |
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  | `model_0.pt` ... `model_400.pt` | Intermediate checkpoints every 100 steps |
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+ | `params/deploy.yaml` | Deploy configuration (obs order, action scale, joint mapping) |
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  | `params/env.yaml` | Environment configuration |
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  | `params/agent.yaml` | Agent/PPO configuration |
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  | `events.out.tfevents.*` | TensorBoard training logs |
 
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  ### Deploy in MuJoCo simulator
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  ```bash
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+ # Copy ONNX model + deploy config
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  cp policy.onnx policy.onnx.data \
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  unitree_rl_mjlab/deploy/robots/go2/config/policy/velocity/v0/exported/
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+ cp params/deploy.yaml \
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+ unitree_rl_mjlab/deploy/robots/go2/config/policy/velocity/v0/params/
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+
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+ # Build controller
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+ cd unitree_rl_mjlab/deploy/robots/go2
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+ mkdir -p build && cd build
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+ cmake .. -DCMAKE_BUILD_TYPE=Release && make -j$(nproc)
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  # Run simulator + controller
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  cd unitree_mujoco/simulate/build && ./unitree_mujoco
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  cd unitree_rl_mjlab/deploy/robots/go2/build && ./go2_ctrl --network=lo
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  ```
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+ > **Important:** This model was trained **without `gait_phase`** and with **action scale 0.5**. The default `deploy.yaml` in unitree_rl_mjlab may differ — use `params/deploy.yaml` from this repo.
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+
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  ### Fine-tune on rough terrain
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  ```bash