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Bringing a Natural Language-enabled Virtual Assistant to Industrial Mobile Robots for Learning, Training and Assistance of Manufacturing Tasks

  • Chen LI
  • , Andreas Kornmaaler Hansen
  • , Dimitrios Chrysostomou
  • , Simon Bøgh
  • , Ole Madsen
  • Aalborg Universitet

Publikation: Bidrag til bog/antologi/rapportKonferenceartikel i proceedingpeer review

Abstract

Nowadays, industrial companies want to enhance their Industry 4.0 competencies. Therefore, they need to help employees master state-of-the-art technologies and gain the necessary knowledge to stay relevant and competitive. As a result, there is a global demand for learning and training tools that assist the employees at all levels. In this paper, we propose a natural language-enabled virtual assistant (VA) integrated with an industrial mobile manipulator to fulfill this target in manufacturing tasks. The latest Learning, Training, Assistance - Formats, Issues, Tools (LTA-FIT) model is leveraged to guide the design and development of a pilot version of the VA. To validate its performance, three manufacturing scenarios are analyzed based on the learning, training, and
assistance phases, respectively. In our system, the human-robot interaction is achieved through conversation and a dashboard implemented as a web application. This intuitive interaction enables operators of all levels to control a industrial mobile manipulator easier and use it as a complementary tool for
developing their competencies. The pilot experiments show that the proposed VA is able to respond to operator commands flexibly within the LTA-FIT model.
OriginalsprogEngelsk
Titel2022 IEEE/SICE International Symposium on System Integration (SII)
Antal sider6
ForlagIEEE
Publikationsdato16 feb. 2022
Sider238-243
ISBN (Elektronisk)9781665445405
DOI
StatusUdgivet - 16 feb. 2022

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