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observation.state
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This dataset was created using LeRobot.

Dataset Structure

meta/info.json:

{
    "codebase_version": "v2.0",
    "robot_type": "aloha",
    "total_episodes": 101,
    "total_frames": 45500,
    "total_tasks": 1,
    "total_videos": 404,
    "total_chunks": 1,
    "chunks_size": 1000,
    "fps": 50,
    "splits": {
        "train": "0:101"
    },
    "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
    "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
    "features": {
        "observation.images.cam_high": {
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            "shape": [
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                "height",
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                "has_audio": false
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        },
        "observation.images.cam_left_wrist": {
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            "shape": [
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            "names": [
                "height",
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            "video_info": {
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        "observation.images.cam_low": {
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            "video_info": {
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                "video.is_depth_map": false,
                "has_audio": false
            }
        },
        "observation.images.cam_right_wrist": {
            "dtype": "video",
            "shape": [
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            "names": [
                "height",
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            ],
            "video_info": {
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                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "has_audio": false
            }
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
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            "names": {
                "motors": [
                    "left_waist",
                    "left_shoulder",
                    "left_elbow",
                    "left_forearm_roll",
                    "left_wrist_angle",
                    "left_wrist_rotate",
                    "left_gripper",
                    "right_waist",
                    "right_shoulder",
                    "right_elbow",
                    "right_forearm_roll",
                    "right_wrist_angle",
                    "right_wrist_rotate",
                    "right_gripper"
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        },
        "observation.effort": {
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            "names": {
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                    "left_elbow",
                    "left_forearm_roll",
                    "left_wrist_angle",
                    "left_wrist_rotate",
                    "left_gripper",
                    "right_waist",
                    "right_shoulder",
                    "right_elbow",
                    "right_forearm_roll",
                    "right_wrist_angle",
                    "right_wrist_rotate",
                    "right_gripper"
                ]
            }
        },
        "action": {
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            "shape": [
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            "names": {
                "motors": [
                    "left_waist",
                    "left_shoulder",
                    "left_elbow",
                    "left_forearm_roll",
                    "left_wrist_angle",
                    "left_wrist_rotate",
                    "left_gripper",
                    "right_waist",
                    "right_shoulder",
                    "right_elbow",
                    "right_forearm_roll",
                    "right_wrist_angle",
                    "right_wrist_rotate",
                    "right_gripper"
                ]
            }
        },
        "episode_index": {
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            "names": null
        },
        "frame_index": {
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        "timestamp": {
            "dtype": "float32",
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        },
        "next.done": {
            "dtype": "bool",
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                1
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        "index": {
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        },
        "task_index": {
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            "names": null
        }
    }
}

Citation

BibTeX:

@article{Zhao2023LearningFB,
    title={Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware},
    author={Tony Zhao and Vikash Kumar and Sergey Levine and Chelsea Finn},
    journal={RSS},
    year={2023},
    volume={abs/2304.13705},
    url={https://arxiv.org/abs/2304.13705}
}
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