eval_frazier_v2

该数据集是使用LeRobot创建的，专为机器人学任务设计，特别是针对so_follower机器人类型。它包含30个episodes，总计10081个frames，覆盖1个任务。数据以parquet格式存储，视频以mp4格式存储，帧率为30fps。数据集的特征包括：动作（action）和观察状态（observation.state），两者均为6维浮点数组，表示机器人的关节位置（如肩部平移、肩部提升、肘部弯曲、腕部弯曲、腕部滚动和夹爪位置）；两个图像观察特征（observation.images.gripper和observation.images.side），均为视频格式，分辨率为480x640，3通道，用于捕捉夹爪和侧面的视觉信息；以及辅助特征如时间戳、帧索引、episode索引、索引和任务索引。该数据集适用于机器人控制、强化学习和视觉-动作映射等研究。This dataset is created using LeRobot and is specifically designed for robotics tasks, particularly for the so_follower robot type. It contains 30 episodes, totaling 10081 frames, covering 1 task. The data is stored in parquet format, with videos in mp4 format at a frame rate of 30fps. The features of the dataset include: action and observation.state, both as 6-dimensional floating-point arrays representing the robots joint positions (such as shoulder translation, shoulder lift, elbow bend, wrist bend, wrist roll, and gripper position); two image observation features (observation.images.gripper and observation.images.side), both in video format with a resolution of 480x640 and 3 channels, used to capture visual information from the gripper and side views; and auxiliary features such as timestamps, frame index, episode index, index, and task index. This dataset is suitable for research in robot control, reinforcement learning, and vision-action mapping.