# RoboCerebra

[RoboCerebra](https://robocerebra-project.github.io/) is a long-horizon manipulation benchmark for evaluating high-level reasoning, planning, and memory in VLAs. Episodes chain multiple sub-goals with language-grounded intermediate instructions, building on top of LIBERO's simulator stack.

- Paper: [RoboCerebra: A Large-scale Benchmark for Long-horizon Robotic Manipulation Evaluation](https://arxiv.org/abs/2506.06677)
- Project website: [robocerebra-project.github.io](https://robocerebra-project.github.io/)
- Dataset: [`lerobot/robocerebra_unified`](https://huggingface.co/datasets/lerobot/robocerebra_unified) — LeRobot v3.0, 6,660 episodes (571,116 frames) at 20 fps, 1,728 language-grounded sub-tasks

## Installation

RoboCerebra reuses LIBERO's simulator stack, so install the `libero` extra:

```bash
pip install -e ".[libero]"
```

<Tip>
RoboCerebra requires Linux (MuJoCo/robosuite). Set the rendering backend before training or evaluation:

```bash
export MUJOCO_GL=egl  # for headless servers
```

</Tip>

## Evaluation

RoboCerebra eval runs against the LIBERO `libero_10` long-horizon suite with RoboCerebra's camera naming (`image` + `wrist_image`) and an extra empty-camera slot for policies expecting three views:

```bash
lerobot-eval \
  --policy.path=pepijn223/smolvla_robocerebra \
  --env.type=libero \
  --env.task=libero_10 \
  --eval.batch_size=1 \
  --eval.n_episodes=10 \
  '--rename_map={"observation.images.image": "observation.images.camera1", "observation.images.wrist_image": "observation.images.camera2"}' \
  --policy.empty_cameras=3
```

## Training

The unified dataset at [`lerobot/robocerebra_unified`](https://huggingface.co/datasets/lerobot/robocerebra_unified) exposes two RGB streams:

| Feature                          | Shape         | Description          |
| -------------------------------- | ------------- | -------------------- |
| `observation.images.image`       | (256, 256, 3) | Third-person view    |
| `observation.images.wrist_image` | (256, 256, 3) | Wrist-mounted camera |
| `observation.state`              | (8,)          | Joint pos + gripper  |
| `action`                         | (7,)          | EEF delta + gripper  |

Fine-tune a SmolVLA base on it:

```bash
lerobot-train \
  --policy.path=lerobot/smolvla_base \
  --dataset.repo_id=lerobot/robocerebra_unified \
  --env.type=libero \
  --env.task=libero_10 \
  --output_dir=outputs/smolvla_robocerebra
```