构建施工机器人通用动作词典，让机器人学会人类施工技能。
A Taxonomy of Construction Task Activities for Robot Workers
- 基于91项职业任务和30段实操视频，提炼41个基础动作单元。
- 将动作分为12组3类，支持参数化组合成可复用的机器人技能。
- 适用于开发通用施工机器人，提升人机协作与技能迁移能力。
近期的视觉-语言-动作模型为机器人提供了超越传统专用系统的广泛技能潜力。然而，施工场景部署需要精确掌握工人活动及其执行所需的能力。本文提出TARCAT，一个基于91项来自七个高就业施工职业的O*NET任务及30段物理工作教学视频的职业基础分类体系。TARCAT定义了41个动作原语，分属12个组别和三个类别，并提供机制将参数化的原语序列组合为可重用技能。该人类可理解的结构可用于组织示范数据、明确机器人需求，以及支持能检索和扩展技能库的编码代理。我们在DOBOT CR3机械臂与CRAFT手爪上验证了部分原语的有效性。TARCAT因此为分析人类工作与开发通用施工机器人提供了共同语言。标注数据可在https://github.com/AICPS/TARCAT-Taxonomy获取。
原文摘要 · Abstract (English)
Recent vision-language-action models offer a path toward robots with broader repertoires than conventional task-specific systems. Construction deployment, however, requires a precise inventory of worker activities and the capabilities needed to execute them. We present TARCAT, an occupation-grounded taxonomy derived from 91 O*NET tasks across seven high-employment construction occupations and 30 instructional videos of physical work. TARCAT defines 41 action primitives in 12 groups and three classes and provides a mechanism for composing parameterized primitive sequences into reusable skills. This human-interpretable structure can organize demonstrations, specify robot requirements, and support coding agents that retrieve and extend skill libraries. We also demonstrate selected primitives on a DOBOT CR3 arm with a CRAFT hand. TARCAT thereby provides a common vocabulary for analyzing human work and developing general-purpose construction robots. Annotations are available at https://github.com/AICPS/TARCAT-Taxonomy.
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