add LeRobot ACT notebook

notebooks/lerobot_act/README.md

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+# ACT Policy → OpenVINO IR Conversion (Notebook Guide)
+
+This README documents the current workflow implemented in `act_to_openvino.ipynb` for converting a LeRobot ACT (Action Chunking Transformer) PyTorch checkpoint into an OpenVINO IR (XML/BIN) model. The notebook presently performs FP32 export (Model Optimizer invoked with FP16 compression flag but output standardized to `act_model_fp32.xml/bin`).
+
+
+## Required Checkpoint Files (`act_checkpoint/`)
+Place these next to the notebook:
+* `model.safetensors` – ACT weights
+* `config.json` – architecture + feature definitions
+* `train_config.json` – optional (reproducibility record)
+* `stats.json` – optional normalization statistics
+
+## Minimal Installation & Launch
+Recommended (Conda environment):
+```bash
+conda create -n unitree_lerobot python=3.10 -y
+conda activate unitree_lerobot
+# Optional helper script if present in this folder
+bash setup_unitree_lerobot_env.sh
+# Launch notebook with correct kernel
+jupyter lab act_to_openvino.ipynb --NotebookApp.kernel_name=unitree_lerobot
+```
+
+If you skip creating a dedicated environment, the dependency cell will install core packages (torch, openvino, nncf, etc.) into the current kernel. You MUST still install `lerobot` manually; the notebook will not auto‑install it.
+
+
+## Key Configuration Variables
+| Variable          | Meaning                                                  |
+|-------------------|----------------------------------------------------------|
+| `CKPT_DIR`        | Relative checkpoint folder (`act_checkpoint`)            |
+| `CHECKPOINT_PATH` | Path to `model.safetensors` (env‑overrideable)           |
+| `IR_OUTPUT_DIR`   | Destination for `model.onnx` & IR artifacts              |
+| `STATS_PATH`      | Path to `stats.json` if present                          |
+| `PRECISIONS`      | Currently `['FP32']`                                     |
+| `TARGET_DEVICE`   | Default runtime device                                   |
+
+## ONNX Export
+Wrapper (`ONNXWrapper`) mirrors ACT forward usage by constructing a batch dict. Input ordering:
+`observation.state`, each camera image (`observation.images.*`), `action_is_pad`, `action`, optional `observation.environment_state`.
+* Output name: `output`
+Exports only if `openvino_ir_outputs/model.onnx` does not already exist.
+
+## Model Optimizer Conversion
+Executed command:
+```
+mo --input_model openvino_ir_outputs/model.onnx --output_dir openvino_ir_outputs --compress_to_fp16=False
+```
+Artifacts are copied / renamed to:
+* `act_model_fp32.xml`
+* `act_model_fp32.bin`
+
+## Directory Layout After Successful Conversion
+```
+act_to_openvino.ipynb
+act_checkpoint/
+  model.safetensors
+  config.json
+  train_config.json
+  stats.json (optional)
+openvino_ir_outputs/
+  model.onnx
+  act_model_fp32.xml
+  act_model_fp32.bin
+```