Datasetpublic

lerobot/aloha_sim_insertion_scripted_image

This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.0", "robot_type": "aloha", "total_episodes": 50, "total_frames": 20000, "total_tasks": 1, "total_videos": 0, "total_chunks": 1, "chunks_size": 1000, "fps": 50, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": null, "features": {… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/aloha_sim_insertion_scripted_image.

sourceHugging Facemitupdated 4mo agoView on Hugging Face

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Dataset Card

This dataset was created using LeRobot.

Dataset Description

—Homepage: https://tonyzhaozh.github.io/aloha/
—Paper: https://arxiv.org/abs/2304.13705
—License: mit

Dataset Structure

meta/info.json:

json

{
    "codebase_version": "v2.0",
    "robot_type": "aloha",
    "total_episodes": 50,
    "total_frames": 20000,
    "total_tasks": 1,
    "total_videos": 0,
    "total_chunks": 1,
    "chunks_size": 1000,
    "fps": 50,
    "splits": {
        "train": "0:50"
    },
    "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
    "video_path": null,
    "features": {
        "observation.images.top": {
            "dtype": "image",
            "shape": [
                480,
                640,
                3
            ],
            "names": [
                "height",
                "width",
                "channel"
            ]
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                14
            ],
            "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"
                ]
            }
        },
        "action": {
            "dtype": "float32",
            "shape": [
                14
            ],
            "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": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "frame_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "timestamp": {
            "dtype": "float32",
            "shape": [
                1
            ],
            "names": null
        },
        "next.done": {
            "dtype": "bool",
            "shape": [
                1
            ],
            "names": null
        },
        "index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "task_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        }
    }
}

Citation

BibTeX:

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}
}