RoboMME
Collection
Benchmarking memory-augmented robotic generalist policies • 15 items • Updated • 2
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RoboMME Training Data (H5 format)
Arxiv Paper | HF Paper | Website | Benchmark Code | Policy Learning Code
H5 format of RoboMME training data. There are a total of 16 tasks, each with 100 episodes.
.
├── README.md
├── record_dataset_BinFill.h5.tar.xz
├── record_dataset_ButtonUnmask.h5.tar.xz
├── record_dataset_ButtonUnmaskSwap.h5.tar.xz
├── record_dataset_InsertPeg.h5.tar.xz
├── record_dataset_MoveCube.h5.tar.xz
├── record_dataset_PatternLock.h5.tar.xz
├── record_dataset_PickHighlight.h5.tar.xz
├── record_dataset_PickXtimes.h5.tar.xz
├── record_dataset_RouteStick.h5.tar.xz
├── record_dataset_StopCube.h5.tar.xz
├── record_dataset_SwingXtimes.h5.tar.xz
├── record_dataset_VideoPlaceButton.h5.tar.xz
├── record_dataset_VideoPlaceOrder.h5.tar.xz
├── record_dataset_VideoRepick.h5.tar.xz
├── record_dataset_VideoUnmask.h5.tar.xz
└── record_dataset_VideoUnmaskSwap.h5.tar.xz
For more information about dataset usage, please refer to https://github.com/RoboMME/robomme_benchmark?tab=readme-ov-file#-training-data
We also provide other formats of RoboMME training data for people to use:
- Pickle format, which is used in our MME-VLA experiments.
- Lerobot format, which is used in our Diffusion Policy experiments.
- TensorFlow Dataset format, which is used in our MemoryVLA experiments.
After donwload this dataset, run
python tarxz_h5.py decompress --input_dir <robomme_data_h5_dir> --jobs 16 --remove_archive
to extract the xz files.
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