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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`_ |