Human–robot co-working is a promising autonomous resolution for alleviating the sufferings from labor shortage, occupational hazards, and low productivity. Instructing robots to complete construction tasks using natural language (NL) is a hand-free and straightforward working method, requiring less expertise. Towards fluent intention communication, ontology serves as an important knowledge base for the robot to intelligently understand NL instructions. However, few studies utilized ontology to facilitate a natural-language-based human–robot interaction in construction applications before. This preliminary study designs an integrated ontology for natural language-instructed excavation tasks. Then, a validation framework with a use case illustration is presented for evaluating the ontology from a reasoning perspective. This paper is expected to demonstrate the feasibility of controlling robots to complete on-site construction tasks through NL instructions.
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Hong et al. (2024) studied this question.
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