A Taxonomy of Construction Task Activities for Robot Workers
Authors: Sadman Sakib, Zhangyi None Peng, Yujie Pang, Yu Otsuki, Mohammad Abdullah Al Faruque
Organizations: The authors are with the Nhu Department of Electrical Engineering and Computer Science, University of California-Irvine, Irvine, CA, USA · The authors contributed during the UCInspire program · The author is with the Department of Civil and Environmental Engineering, University of California-Irvine, Irvine, CA, USA
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.