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The introduction of robots is widely considered to have significant potentialof alleviating the issues of worker shortage and stagnant productivity thatafflict the construction industry. However, it is challenging to use fullyautomated robots in complex and unstructured construction sites. Human-RobotCollaboration (HRC) has shown promise of combining human workers' flexibilityand robot assistants' physical abilities to jointly address the uncertaintiesinherent in construction work. When introducing HRC in construction, it iscritical to recognize the importance of teamwork and supervision in fieldconstruction and establish a natural and intuitive communication system for thehuman workers and robotic assistants. Natural language-based interaction canenable intuitive and familiar communication with robots for human workers whoare non-experts in robot programming. However, limited research has beenconducted on this topic in construction. This paper proposes a framework toallow human workers to interact with construction robots based on naturallanguage instructions. The proposed method consists of three stages: NaturalLanguage Understanding (NLU), Information Mapping (IM), and Robot Control (RC).Natural language instructions are input to a language model to predict a tagfor each word in the NLU module. The IM module uses the result of the NLUmodule and building component information to generate the final instructionaloutput essential for a robot to acknowledge and perform the construction task.A case study for drywall installation is conducted to evaluate the proposedapproach. The obtained results highlight the potential of using naturallanguage-based interaction to replicate the communication that occurs betweenhuman workers within the context of human-robot teams.

Natural Language Instructions for Intuitive Human Interaction with Robotic Assistants in Field Construction Work