Skip to main navigation Skip to search Skip to main content

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 University

Research output: Chapter in Book/Report/Conference proceedingConference contribution to 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.
Original languageEnglish
Title of host publication2022 IEEE/SICE International Symposium on System Integration (SII)
Number of pages6
PublisherIEEE
Publication date16 Feb 2022
Pages238-243
ISBN (Electronic)9781665445405
DOIs
Publication statusPublished - 16 Feb 2022

Fingerprint

Dive into the research topics of 'Bringing a Natural Language-enabled Virtual Assistant to Industrial Mobile Robots for Learning, Training and Assistance of Manufacturing Tasks'. Together they form a unique fingerprint.

Cite this