In the context of robot learning for manipulation, curated datasets are an important resource for advancing the state of the art; however, available datasets typically only include successful executions or are focused on one particular type of skill. In this short paper, we briefly describe a dataset of various skills performed in the context of coffee preparation. The dataset, which we call COFFAIL, includes both successful and anomalous skill execution episodes collected with a physical robot in a kitchen environment, a couple of which are performed with bimanual manipulation. In addition to describing the data collection setup and the collected data, the paper illustrates the use of the data in COFFAIL to learn a robot policy using imitation learning.

翻译：在机器人学习与操作领域，精心整理的数据集是推动技术发展的重要资源。然而，现有数据集通常仅包含成功执行案例，或集中于特定类型的技能。本文简要描述了一套在咖啡制备过程中执行多种技能的数据集。该数据集（命名为COFFAIL）包含了在厨房环境中使用实体机器人收集的成功与异常技能执行序列，其中部分涉及双臂操作。除介绍数据采集设置与所收集数据外，本文还展示了如何利用COFFAIL数据集通过模仿学习方法训练机器人策略的应用案例。