---
library_name: pytorch
language:
- en
tags:
- robotics
- robodojo
- vision-language-action
- meituan-robotics
---

# Meituan Robotics 0

[Technical Report](https://arxiv.org/abs/2611.08577)

A RoboDojo dual-arm vision-language-action policy with episode-first RGB and three seconds of CD-LAM visual memory. It predicts 50 actions and executes 16, using continuous gripper widths.

Inference and evaluation use the **Meituan_Robotics_0** adapter in [XPolicyLab](https://github.com/XPolicyLab/XPolicyLab/tree/main/policy/Meituan_Robotics_0). Use the matching adapter supporting the layout below.

## Model files

```text
base_vlm/                 # Qwen configuration, tokenizer and processor only
cdlam/model.pt            # Frozen visual-memory encoder
checkpoints/model.pt      # Complete VLA checkpoint, including VLM weights
config.yaml               # Inference configuration
dataset_statistics.json   # State/action normalization
```

The VLM parameters are already included in `checkpoints/model.pt`; no separate base-VLM weights or training initialization are required.

## Load

Download this repository, install the policy dependencies following the [XPolicyLab adapter README](https://github.com/XPolicyLab/XPolicyLab/blob/main/policy/Meituan_Robotics_0/README.md), and run from a RoboDojo workspace with `XPolicyLab` importable. Python 3.11 and a CUDA GPU are required.

```python
import os
from XPolicyLab.policy.Meituan_Robotics_0.model import Model

os.environ["ROBODOJO_ASSET_ROOT"] = "/path/to/downloaded/model-repository"
policy = Model({
    "bench_name": "RoboDojo", "task_name": "stack_bowls",
    "env_cfg_type": "arx_x5", "action_type": "joint",
    "ckpt_name": "mr0", "seed": 0,
})
```

Use XPolicyLab's `eval.sh` for rollouts so that observations are collected at 25 Hz for causal CD-LAM history:

```bash
# From XPolicyLab/, using your existing policy and simulator environments:
export ROBODOJO_ASSET_ROOT=/path/to/downloaded/model-repository
EVAL_ENV_TYPE=sim bash policy/Meituan_Robotics_0/eval.sh \
  RoboDojo stack_bowls mr0 arx_x5 joint 0 \
  0 1 meituan_robotics_0 robodojo
```

See [XPolicyLab](https://github.com/XPolicyLab/XPolicyLab) for installation, supported observations, deployment and evaluation instructions.

## File verification

[SHA256SUMS](SHA256SUMS) is the single SHA-256 checksum manifest for this release. It covers every repository file except the manifest itself, including weights, configuration, tokenizer/processor metadata, and documentation.

After downloading the complete repository, run from its root directory:

```bash
sha256sum -c SHA256SUMS
```