Choi, D., Shi, W., Liang, Y. S., Yeo, K. H., & Kim, J.-J. (2021). Controlling Industrial Robots with High-Level Verbal Commands. Lecture Notes in Computer Science, 216–226. doi:10.1007/978-3-030-90525-5_19
Abstract:
Industrial robots today are still mostly pre-programmed to
perform a specific task. Despite previous research in human-robot interaction
in the academia, adopting such systems in industrial settings is
not trivial and has rarely been done. In this paper, we introduce a robotic
system that we control with high-level verbal commands, leveraging some
of the latest neural approaches to language understanding and a cognitive
architecture for goal-directed but reactive execution. We show that
a large-scale pre-trained language model can be effectively fine-tuned for
translating verbal instructions into robot tasks, better than other semantic
parsing methods, and that our system is capable of handling through
dialogue a variety of exceptions that happen during human-robot interaction
including unknown tasks, user interruption, and changes in the
world state.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A-STAR - AME Programmatic Funding Scheme
Grant Reference no. : A18A2b0046
Description:
This is a post-peer-review, pre-copyedit version of an article published in Social Robotics. The final authenticated version is available online at:
https://doi.org/10.1007/978-3-030-90525-5_19