sort_left_v2_20260607_103022
收藏Hugging Face2026-06-07 更新2026-06-07 收录
下载链接:
https://huggingface.co/datasets/RobotRoger/sort_left_v2_20260607_103022
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资源简介:
这是一个基于LeRobot框架创建的机器人任务数据集,用于训练机器人学习模型。数据集包含机器人执行任务时的动作、状态观测、手腕摄像头图像、时间戳和索引等信息。具体特征包括:动作(6个浮点值,对应肩部、肘部、腕部和夹爪的位置)、观测状态(6个浮点值,与动作相同)、观测图像(手腕摄像头视频,分辨率为480x640,3通道,30帧/秒)、时间戳、帧索引、剧集索引、任务索引等。数据集总共有21个剧集、14074帧、1个任务,数据以Parquet格式存储,视频以MP4格式存储。机器人类型为so_follower。
This is a robot task dataset created based on the LeRobot framework, designed for training robot learning models. The dataset includes information such as actions, state observations, wrist camera images, timestamps, and indices during robot task execution. Specific features include: actions (6 floating-point values corresponding to shoulder, elbow, wrist, and gripper positions), observation states (6 floating-point values, same as actions), observation images (wrist camera video with a resolution of 480x640, 3 channels, 30 frames per second), timestamps, frame indices, episode indices, task indices, etc. The dataset consists of 21 episodes, 14074 frames, and 1 task, with data stored in Parquet format and videos in MP4 format. The robot type is so_follower.
提供机构:
RobotRoger创建时间:
2026-06-07
原始信息汇总
数据集概述:sort_left_v2_20260607_103022
- 许可证:Apache-2.0
- 任务类别:机器人学(Robotics)
- 创建工具:LeRobot
数据集结构
- 帧率:30 FPS
- 总片段数:21
- 总帧数:14,074
- 总任务数:1
- 机器人类型:so_follower
- 数据分割:
train分割包含所有21个片段
特征
| 特征名 | 数据类型 | 形状 | 注释 |
|---|---|---|---|
action |
float32 | (6,) | 6个动作维度:肩部旋转、肩部升降、肘部弯曲、腕部弯曲、腕部旋转、夹爪位置 |
observation.state |
float32 | (6,) | 6个状态维度,与action的维度名称相同 |
observation.images.wrist |
video | (480, 640, 3) | 腕部摄像头视频,分辨率480x640,3通道,AV1格式,30 FPS |
timestamp |
float32 | (1,) | 时间戳 |
frame_index |
int64 | (1,) | 帧索引 |
episode_index |
int64 | (1,) | 片段索引 |
index |
int64 | (1,) | 全局索引 |
task_index |
int64 | (1,) | 任务索引 |
文件信息
- 数据文件大小:约100 MB
- 视频文件大小:约200 MB
- 数据文件路径格式:
data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet - 视频文件路径格式:
videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4
引用信息
- 文献引用:暂无提供具体引用信息。



