oxe-auge/fractal20220817_data_train_22500_25000_augmented

fractal20220817_data_train_22500_25000_augmented是一个用于机器人增强学习和跨实体策略学习的大规模数据集。数据集包含了多种机器人（如jaco、kinova3、kuka_iiwa、panda、sawyer、ur5e、xarm7）的图像、关节位置、末端执行器位置等信息，并且提供了自然语言指令。数据集的特征包括原始机器人的图像、增强后的机器人图像、末端执行器位置误差、关节角度等。数据集的总帧数为108,522，总episodes为2,500，帧率为3fps。数据以parquet格式存储，分割为train集。

fractal20220817_data_train_22500_25000_augmented is a large-scale dataset for robotic augmentation learning and cross-embodiment policy learning. The dataset includes images, joint positions, end-effector positions, and other information for various robots (e.g., jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7), along with natural language instructions. The features of the dataset include original robot images, augmented robot images, end-effector position errors, joint angles, etc. The dataset contains a total of 108,522 frames, 2,500 episodes, and has a frame rate of 3fps. The data is stored in parquet format and split into a train set.