metadata
license: cc-by-nc-4.0
task_categories:
- robotics
language:
- en
tags:
- robotics
- manipulation
- multimodal
- vla
- acoustic
- thermal
- radar
size_categories:
- 10K<n<100K
pretty_name: MuseVLA Dataset
arxiv:
- 2606.17598
MuseVLA Dataset
Multi-modal robot manipulation dataset with synchronized RGB, depth, acoustic,
thermal, and radar streams. Released as two parts (dataset_01/,
dataset_02/) sharing the same per-episode layout. Together they cover
~1400 episodes across 11 instructions (towel / clothes / box / item / drink
manipulation).
Per-episode contents
{episode_name}/
├── video.mp4 # RGB, 1280×720, 30 fps
├── mask/video.mp4 # SAM3 segmentation mask
├── depth/images/ # depth jpgs
├── acoustic/{images,images_masked}/ # spectrogram + 3 overlay variants
├── radar/{images,images_masked}/ # radar + 3 overlay variants
├── thermal/{left,right,images,images_masked}/ # left / right / merged / overlays
├── 6d_pose/right_arm.npy # end-effector trajectory
├── arm_command/, arm_status/, ee_command/, hand_status/ # control signals
Annotations live under *_labels/{episode}.json with per-segment
instruction, start, end, plus _validity.json recording SAM3 validity.
Top-level instructions_all.json, valid_samples.json, and
statistics_6dpose_delta_NRt0.json are provided for indexing and
normalization.
Statistics
| Episodes | Valid | Annotated segments | Unique instructions | RGB | Frame rate |
|---|---|---|---|---|---|
| 1397 (1279 + 118) | 1010 (913 + 97) | 1930 (1737 + 193) | 11 | 1280 × 720 | 30 fps |
Citation
@misc{liu2026musevlaadaptivemultimodalsensing,
title={MuseVLA: An Adaptive Multimodal Sensing Vision-Language-Action Model for Robotic Manipulation},
author={Xingyuming Liu and Ruichun Ma and Heyu Guo and Qixiu Li and Qingwen Yang and Lin Luo and Shiqi Jiang and Chenren Xu and Jiaolong Yang and Baining Guo},
year={2026},
eprint={2606.17598},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2606.17598},
}
License
CC-BY-NC-4.0 (research use only).