构建咖啡制作场景的机器人成功与异常操作数据集，支持模仿学习。
COFFAIL: A Dataset of Successful and Anomalous Robot Skill Executions in the Context of Coffee Preparation
- 在厨房环境中采集物理机器人执行咖啡制作任务的正负样本
- 包含双手协作操作，覆盖成功与异常执行片段
- 可用于训练鲁棒的机器人操纵策略，适合具身智能研究者
在机器人操纵学习领域，精心设计的数据集是推动技术进步的重要资源；然而现有数据集通常仅包含成功执行案例，或局限于特定技能类型。本文简要介绍一个名为COFFAIL的新型数据集，涵盖咖啡制备场景下的多种技能执行，包括成功与异常的完整执行片段。数据由真实机器人在厨房环境中采集，部分任务采用双臂协同操作。本文还展示了如何利用COFFAIL数据集通过模仿学习训练机器人策略，验证其在复杂现实场景中的应用潜力。
原文摘要 · Abstract (English)
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.
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