A novel non-intrusive mental workload evaluation concept in human-robot collaboration

Baixiang Zhao*, Xiu-tian Yan, Jörn Mehnen

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

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Abstract

The integration of Human-Robot Collaboration (HRC) in industrial robotics introduces challenges, particularly in adapting manufacturing environments to work seamlessly with collaborative robots. A key objective in HRC system optimization is enhancing human acceptance of these robots and improving productivity. Traditionally, the assessment of human mental workload in these settings relies on methods like EEG, fNIRS, and heart rate monitoring, which require direct physical contact and can be impractical in manufacturing environments. To address these issues, we propose an innovative and non-intrusive method that employs cameras to measure mental workload. This technique involves capturing video footage of human operators on the shop floor, focusing specifically on facial expressions. Advanced AI algorithms analyse these videos to predict heart rate ranges, which are then used to estimate mental workload levels in real time. This approach not only circumvents the need for direct contact with measurement devices but also enhances privacy and data security through privacy computing measures. Our proposed method was tested in an HRC experiment to provide preliminary validation. This pioneering use of non-intrusive AI-based vision techniques for real-time mental workload assessment represents a significant advancement in managing human factors in industrial HRC settings.
Original languageEnglish
Article number12002
Number of pages6
JournalMATEC Web of Conferences
Volume401
DOIs
Publication statusPublished - 27 Aug 2024
Event21st International Conference on Manufacturing Research - Glasgow, United Kingdom
Duration: 28 Aug 202430 Aug 2024
https://www.icmr.org.uk/

Funding

This research is supported by the EP/V062158/1, the Made Smarter Innovation - Research Centre for Smart, Collaborative Industrial Robotics.

Keywords

  • human-robot collaboration
  • mental workload
  • artifical intelligence
  • video analysis

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