README.md

---
license: mit
tags:
  - robotics
  - lerobot
  - manipulation
  - sim-to-real
  - imitation-learning
task_categories:
  - robotics
---

# Capstone VLA Datasets

LeRobot v2.1 datasets for a liquid pouring task on a **KuavoV4Pro**
humanoid robot (34-DOF, bimanual). Used to benchmark GR00T N1.6,
pi0.5, and Diffusion Policy under varying real-to-synthetic data ratios.

## Mixture Configurations

| Dataset | Type | Episodes |
| ------- | ---- | -------- |
| `sim_mixed_40_60` | unknown | 500 |

## Dataset Structure (LeRobot v2.1)

```
<dataset>/
├── meta/
│   ├── info.json
│   ├── tasks.jsonl
│   ├── episodes.jsonl
│   └── stats.safetensors
├── data/
│   └── chunk-*/
│       └── episode_*.parquet
└── videos/
    └── chunk-*/
        └── observation.images.*_episode_*.mp4
```

## Pipeline

1. **Teleoperation** — ROS + Isaac Lab teleop (real demos)
2. **Mimic annotation** — Isaac Lab Mimic with Pink IK controller
3. **Synthetic generation** — Isaac Lab Mimic (~40% success rate)
4. **Format conversion** — HDF5 → LeRobot v2.1 (parquet + video)
5. **Training** — GR00T N1.6 · pi0.5 · Diffusion Policy

## Benchmarking

Total dataset size held constant at ~600 episodes across all mixture
configurations for controlled comparison.

---
_Auto-generated by `upload_datasets.py`_