  The introduction of robots is widely considered to have significant potential
of alleviating the issues of worker shortage and stagnant productivity that
afflict the construction industry. However, it is challenging to use fully
automated robots in complex and unstructured construction sites. Human-Robot
Collaboration (HRC) has shown promise of combining human workers' flexibility
and robot assistants' physical abilities to jointly address the uncertainties
inherent in construction work. When introducing HRC in construction, it is
critical to recognize the importance of teamwork and supervision in field
construction and establish a natural and intuitive communication system for the
human workers and robotic assistants. Natural language-based interaction can
enable intuitive and familiar communication with robots for human workers who
are non-experts in robot programming. However, limited research has been
conducted on this topic in construction. This paper proposes a framework to
allow human workers to interact with construction robots based on natural
language instructions. The proposed method consists of three stages: Natural
Language Understanding (NLU), Information Mapping (IM), and Robot Control (RC).
Natural language instructions are input to a language model to predict a tag
for each word in the NLU module. The IM module uses the result of the NLU
module and building component information to generate the final instructional
output essential for a robot to acknowledge and perform the construction task.
A case study for drywall installation is conducted to evaluate the proposed
approach. The obtained results highlight the potential of using natural
language-based interaction to replicate the communication that occurs between
human workers within the context of human-robot teams.
