Abstract
Effective and efficient communication is critical for human-robot collaboration and human-agent teaming. This paper presents the design of a Controlled Robot Language (CRL) and its formal grammar for instruction interpretation and automated robot planning. The CRL framework defines a formal language domain that deterministically maps linguistic commands to logical semantic expressions. As compared to Controlled Natural Language, which aims for general knowledge representation, CRL expressions are particularly designed to parse human instructions in automated robot planning. The grammar of CRL is developed in accordance with the IEEE CORA ontology, which defines the majority of formal English domain, accepting large range of intuitive instructions. For sentences outside the grammar coverage, CRL checker is used to detect linguistic patterns, which can be further processed by CRL translator to recover back an equivalent expression in CRL grammar. The final output is formal semantic representation using first-order logic in large discourse. The CRL framework was evaluated on various corpora and it outperformed CRL in balancing coverage and specificity.
This work was partially supported by NSF CMMI 2129113 and WSU URCAF 2019.
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The complete grammar and parsers are available at: https://github.com/hhelium.
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Tran, D., Yan, F., Yihun, Y., Tan, J., He, H. (2021). A Framework of Controlled Robot Language for Reliable Human-Robot Collaboration. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_29
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