five

G1_MountCamera_Dataset

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魔搭社区2025-11-01 更新2025-01-11 收录
下载链接:
https://modelscope.cn/datasets/unitreerobotics/G1_MountCamera_Dataset
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资源简介:
This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 - **Task Objective:** Place the OAK-D-LITE camera into the mounting case and secure the lid. - **Operational Objects:** An OAK-D-LITE camera along with its original complete packaging (Purchase link: [【淘宝】7天无理由退货 https://e.tb.cn/h.606wnDDmrTMhcch?tk=Dr7feJHVOyp CZ009 「OpenCV AI视觉套件 OAK-D-Lite智能开发 深度摄像头RGB高清相机」点击链接直接打开 或者 淘宝搜索直接打开]) - **Operation Duration:** Each operation takes approximately 40 seconds. - **Recording Frequency:** 30 Hz. - **Robot Type:** 7-DOF dual-arm G1 robot. - **End Effector:** Three-fingered dexterous hands. - **Dual-Arm Operation:** Yes. - **Image Resolution:** 640x480. - **Camera Positions:** Wrist-mounted (monocular camera) + head-mounted (binocular cameras). - **Data Content:** • Robot's current state. • Robot's next action. • Current camera view images. - **Robot Initial Posture:** The first robot state in each dataset entry. - **Object Placement:** PPosition the camera case at the midpoint between the robot's arms in their initial state (arms vertical), 20cm away from the inner edge of the table's wall (robot-facing side). Place the camera on the right side of the case, and position the lid on the left side of the case. - **Camera View:** Follow the guidelines in **Part 5** of [AVP Teleoperation Documentation](https://github.com/unitreerobotics/avp_teleoperate). - **Important Notes:** 1. Due to the inability to precisely describe spatial positions, adjust the scene to closely match the first frame of the dataset after installing the hardware as specified in **Part 5** of [AVP Teleoperation Documentation](https://github.com/unitreerobotics/avp_teleoperate). 2. Data collection is not completed in a single session, and variations between data entries exist. Ensure these variations are accounted for during model training. ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "Unitree_G1", "total_episodes": 351, "total_frames": 389708, "total_tasks": 1, "total_videos": 1404, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:351" }, "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.state": { "dtype": "float32", "shape": [ 16 ], "names": [ [ "kLeftShoulderPitch", "kLeftShoulderRoll", "kLeftShoulderYaw", "kLeftElbow", "kLeftWristRoll", "kLeftWristPitch", "kLeftWristyaw", "kRightShoulderPitch", "kRightShoulderRoll", "kRightShoulderYaw", "kRightElbow", "kRightWristRoll", "kRightWristPitch", "kRightWristYaw", "kLeftGripper", "kRightGripper" ] ] }, "action": { "dtype": "float32", "shape": [ 16 ], "names": [ [ "kLeftShoulderPitch", "kLeftShoulderRoll", "kLeftShoulderYaw", "kLeftElbow", "kLeftWristRoll", "kLeftWristPitch", "kLeftWristyaw", "kRightShoulderPitch", "kRightShoulderRoll", "kRightShoulderYaw", "kRightElbow", "kRightWristRoll", "kRightWristPitch", "kRightWristYaw", "kLeftGripper", "kRightGripper" ] ] }, "observation.images.cam_left_high": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_right_high": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_left_wrist": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_right_wrist": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

本数据集基于[LeRobot](https://github.com/huggingface/lerobot)构建。 ## 数据集说明 - **主页:** [更多信息待补充] - **论文:** [更多信息待补充] - **许可证:** apache-2.0 - **任务目标:** 将OAK-D-LITE摄像头(OAK-D-LITE)安装至配套安装盒中并锁紧盒盖。 - **操作对象:** OAK-D-LITE摄像头(OAK-D-LITE)及其全套原厂包装(购买链接:【淘宝】7天无理由退货 https://e.tb.cn/h.606wnDDmrTMhcch?tk=Dr7feJHVOyp CZ009 「OpenCV AI视觉套件 OAK-D-Lite智能开发 深度摄像头RGB高清相机」点击链接直接打开 或 直接通过淘宝搜索获取) - **操作时长:** 单次操作耗时约40秒。 - **录制帧率:** 30 Hz。 - **机器人类型:** 7自由度双臂G1机器人(G1) - **末端执行器:** 三指灵巧手。 - **双臂操作:** 是。 - **图像分辨率:** 640×480。 - **摄像头安装位置:** 腕部安装(单目摄像头)+ 头部安装(双目摄像头)。 - **数据内容:** • 机器人当前状态 • 机器人待执行的下一动作 • 当前摄像头采集的画面图像 - **机器人初始姿态:** 每个数据条目的首个机器人状态。 - **物体摆放要求:** 将摄像头安装盒放置于机器人初始双臂垂直状态时的双臂中点位置,距离桌面朝向机器人一侧的内壁内缘20cm处;将摄像头置于安装盒右侧,盒盖置于安装盒左侧。 - **摄像头视角:** 遵循[AVP遥操作文档](https://github.com/unitreerobotics/avp_teleoperate)第5部分的指南。 - **重要注意事项:** 1. 由于无法精准描述空间位置,在按照[AVP遥操作文档](https://github.com/unitreerobotics/avp_teleoperate)第5部分完成硬件安装后,请调整场景至与数据集首帧高度匹配。 2. 数据采集并非单次完成,不同数据条目间存在差异,在模型训练阶段需充分考虑此类差异。 ## 数据集结构 [meta/info.json]: json { "codebase_version": "v2.0", "robot_type": "Unitree_G1", "total_episodes": 351, "total_frames": 389708, "total_tasks": 1, "total_videos": 1404, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:351" }, "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.state": { "dtype": "float32", "shape": [ 16 ], "names": [ [ "kLeftShoulderPitch", "kLeftShoulderRoll", "kLeftShoulderYaw", "kLeftElbow", "kLeftWristRoll", "kLeftWristPitch", "kLeftWristyaw", "kRightShoulderPitch", "kRightShoulderRoll", "kRightShoulderYaw", "kRightElbow", "kRightWristRoll", "kRightWristPitch", "kRightWristYaw", "kLeftGripper", "kRightGripper" ] ] }, "action": { "dtype": "float32", "shape": [ 16 ], "names": [ [ "kLeftShoulderPitch", "kLeftShoulderRoll", "kLeftShoulderYaw", "kLeftElbow", "kLeftWristRoll", "kLeftWristPitch", "kLeftWristyaw", "kRightShoulderPitch", "kRightShoulderRoll", "kRightShoulderYaw", "kRightElbow", "kRightWristRoll", "kRightWristPitch", "kRightWristYaw", "kLeftGripper", "kRightGripper" ] ] }, "observation.images.cam_left_high": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_right_high": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_left_wrist": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_right_wrist": { "dtype": "video", "shape": [ 3, 480, 640 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ## 引用 **BibTeX:** bibtex [More Information Needed]
提供机构:
maas
创建时间:
2025-01-06
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