COFFAIL：咖啡准备情境中成功与异常机器人技能执行数据集
COFFAIL: A Dataset of Successful and Anomalous Robot Skill Executions in the Context of Coffee Preparation
AI总结：
本文提出COFFAIL数据集，包含厨房环境中机器人成功与异常咖啡制作技能执行数据，用于通过模仿学习训练机器人策略。
摘要：
在机器人操作学习的背景下，精心编纂的数据集是推动前沿的重要资源；然而，现有数据集通常只包含成功的执行或专注于特定类型技能。在本文简短的论文中，我们简要描述了一个在咖啡准备情境中执行各种技能的数据集。该数据集称为COFFAIL，包含在厨房环境中使用物理机器人收集的成功和异常技能执行片段，其中一些涉及双臂操作。除了描述数据收集设置和收集的数据外，本文还展示了如何利用COFFAIL数据通过模仿学习训练机器人策略。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
