Datasets:

openbmb
/

MiniCPM-RobotManip-LIBERO

license: apache-2.0
task_categories:
  - robotics
tags:
  - LeRobot
  - LIBERO
  - robotics
  - vision-language-action
  - MiniCPM-RobotManip
configs:
  - config_name: default
    data_files: '*/data/*/*.parquet'

MiniCPM-RobotManip LIBERO

This dataset contains the four LIBERO suites converted to LeRobot v3 format for the MiniCPM-RobotManip LIBERO full-parameter fine-tuning example in starVLA.

Dataset summary

Suite	Episodes	Frames	Videos
LIBERO-10	358	95,740	716
LIBERO-Goal	405	48,131	810
LIBERO-Object	450	66,294	900
LIBERO-Spatial	423	51,707	846
Total	1,636	261,872	3,272

Format: LeRobot v3
Frequency: 20 Hz
Cameras: agent view and wrist view
Video resolution: 256 × 256
Action target: observation.xvla_abs_ee6d
Action target dimension: 10

EE6D target

observation.xvla_abs_ee6d contains an absolute single-arm target:

[0:3]: xyz position
[3:9]: rotation6D
[9]: gripper closed (0 = open, 1 = closed)

The starVLA MiniCPM-RobotManip recipe uses the current row as state and offsets 1–30 as the action chunk. It maps this 10-D vector to the left-arm [7:17] slot of MiniCPM-RobotManip's unified 80-D state/action space; other channels are masked out of the training loss.

Each suite includes meta/modality.json with the mapping expected by starVLA.

Legacy auxiliary column

The parquet files retain actino.xvla_abs_ee6d, a legacy auxiliary field from the original conversion pipeline. It is intentionally preserved for provenance and is not consumed by the published starVLA recipe. Use observation.xvla_abs_ee6d for both state and offset action targets.

Download

hf download openbmb/MiniCPM-RobotManip-LIBERO \
  --repo-type dataset \
  --local-dir playground/Datasets/LIBERO_EE6D

Expected top-level directories:

libero_10_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
libero_goal_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
libero_object_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
libero_spatial_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/

Training with starVLA

VLM_PATH=openbmb/MiniCPM-RobotManip \
LIBERO_EE6D_ROOT=playground/Datasets/LIBERO_EE6D \
bash examples/modelExtensions/MiniCPM-RobotManip/train_files/run_libero_train.sh

The corresponding public base checkpoint is openbmb/MiniCPM-RobotManip.

Source and processing

The demonstrations originate from the LIBERO benchmark. The four suites were filtered, converted to LeRobot v3 at 20 Hz, and augmented with absolute EE6D targets aligned to each parquet row and video frame. Original observation and action fields are retained.

This release contains simulation demonstrations only. It does not contain personal or human-subject data.

License

Released under the Apache License 2.0. See LICENSE.

Citation

Please cite LIBERO and MiniCPM-Robot when using this dataset:

@inproceedings{liu2023libero,
  title={LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning},
  author={Liu, Bo and Zhu, Yifeng and Gao, Chongkai and Feng, Yihao and Liu, Qiang and Zhu, Yuke and Stone, Peter},
  booktitle={Advances in Neural Information Processing Systems},
  year={2023}
}

For the current MiniCPM-Robot citation, see the MiniCPM-Robot project.