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observation.state
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End of preview. Expand in Data Studio

This dataset was created using LeRobot.

Dataset Description

Repository: X-VLA

License: Apache 2.0

Paper: Zheng et al., 2025, “X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model” (arXiv:2510.10274)

Dataset Structure

meta/info.json:

{
    "codebase_version": "v3.0",
    "robot_type": "franka",
    "total_episodes": 1542,
    "total_frames": 2852512,
    "total_tasks": 1,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 500,
    "fps": 20,
    "splits": {
        "train": "0:1542"
    },
    "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
    "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
    "features": {
        "observation.images.cam_high": {
            "dtype": "video",
            "shape": [
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                640,
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            ],
            "names": [
                "height",
                "width",
                "rgb"
            ],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 20,
                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.images.cam_left_wrist": {
            "dtype": "video",
            "shape": [
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                640,
                3
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            "names": [
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            "info": {
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                "video.width": 640,
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                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
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                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.images.cam_right_wrist": {
            "dtype": "video",
            "shape": [
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            "names": [
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            "info": {
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                "video.width": 640,
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                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                96
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            "names": [
                "eef_euler_0",
                "eef_euler_1",
                "eef_euler_2",
                "eef_euler_3",
                "eef_euler_4",
                "eef_euler_5",
                "eef_euler_6",
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                "eef_euler_11",
                "eef_euler_12",
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                "eef_quat_0",
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                "eef_right_time",
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                "qvel_0",
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        },
        "action": {
            "dtype": "float32",
            "shape": [
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            "names": {
                "motors": [
                    "joint_action_0",
                    "joint_action_1",
                    "joint_action_2",
                    "joint_action_3",
                    "joint_action_4",
                    "joint_action_5",
                    "joint_action_6",
                    "joint_action_7",
                    "joint_action_8",
                    "joint_action_9",
                    "joint_action_10",
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                    "joint_action_13"
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        "time_stamp": {
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        "timestamp": {
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        "frame_index": {
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        "episode_index": {
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        "index": {
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        "task_index": {
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    }
}

Note

The action labels in this dataset have an issue: the left- and right-arm actions are not perfectly synchronized. We recommend re-interpolating them using the provided timestamps. Please refer to our official code for the guidance

Citation

If you find this dataset helpful to your project, please kindly cite us

BibTeX:

@article{zheng2025x,
  title   = {X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model},
  author  = {Zheng, Jinliang and Li, Jianxiong and Wang, Zhihao and Liu, Dongxiu and Kang, Xirui
             and Feng, Yuchun and Zheng, Yinan and Zou, Jiayin and Chen, Yilun and Zeng, Jia and others},
  journal = {arXiv preprint arXiv:2510.10274},
  year    = {2025}
}
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