机器人工人的施工任务活动分类学
A Taxonomy of Construction Task Activities for Robot Workers
- University of California-Irvine（加利福尼亚大学欧文分校）
- UCInspire
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究提出基于职业的TARCAT分类学，定义施工任务的动作基元，在机械臂上演示相关基元，为通用施工机器人开发提供通用词汇。
AI中文摘要：
近期的视觉-语言-动作模型为机器人提供了一条路径，使其拥有比传统任务特定系统更广泛的技能库。然而，施工部署需要对工人活动及执行这些活动所需的能力进行精确梳理。我们提出了TARCAT，这是一种基于职业的分类学，源自7个高就业施工职业的91项O*NET任务和30个体力工作教学视频。TARCAT在12个组和3个类别中定义了41个动作基元，并提供了一种将参数化基元序列组合成可复用技能的机制。这种人类可解释的结构可组织演示、指定机器人需求，并支持检索和扩展技能库的智能体编码。我们还在带有CRAFT手的DOBOT CR3机械臂上演示了选定的基元。TARCAT因此为分析人类工作和开发通用施工机器人提供了通用词汇。注释可在此https URL获取。
英文摘要：
Recent vision-language-action models offer a path toward robots with broader capabilities than conventional task-specific systems. Deploying such systems in construction, 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 task statements across seven high-employment construction occupations and 30 instructional videos. TARCAT defines 41 primitives spanning intellectual, social, and physical categories and provides a mechanism for composing parameterized primitive sequences into reusable skills. This human-interpretable vocabulary supports the specification of robot requirements and enables coding agents to retrieve and extend skill libraries for task execution. We also demonstrate selected primitives on a DOBOT CR3 arm with a CRAFT hand. TARCAT thus provides a common vocabulary for analyzing construction work and developing general-purpose construction robots. Annotations are available at https://github.com/AICPS/TARCAT-Taxonomy.
