Details
| Original language | English |
|---|---|
| Pages (from-to) | 425-428 |
| Number of pages | 4 |
| Journal | CIRP Annals - Manufacturing Technology |
| Volume | 65 |
| Issue number | 1 |
| Publication status | Published - 6 Jan 2016 |
| Externally published | Yes |
Abstract
Automated guided vehicles (AGVs) with autonomous behavior and decentralized human–machine interaction (HMI) are suitable for use in logistics. To facilitate natural interaction, HMI may involve both speech and gesture control. This paper presents a new cognitive approach based on electroencephalography (EEG) for multimodal HMI combining speech and gesture control for AGVs used in logistics. The results indicate that implicit EEG-based measures such as alertness and relaxation significantly affect speech control performance. Consequently, monitoring the user's cognitive workload during logistic operations may lead to a substantial improvement in work performance.
Keywords
- Cognitive robotics, Electroencephalography, Logistics
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: CIRP Annals - Manufacturing Technology, Vol. 65, No. 1, 06.01.2016, p. 425-428.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Multimodal speech and gesture control of AGVs, including EEG-based measurements of cognitive workload
AU - Overmeyer, Ludger
AU - Podszus, Florian
AU - Dohrmann, Lars
N1 - Funding information: The research project that forms the basis for this report is funded under project No. 01MA13005E within the scope of the Autonomics for Industry 4.0 technology program run by the Federal Ministry for Economic Affairs and Energy and is managed by the project management agency “Technical Innovation in Business” at the German Aerospace Center in Cologne. The authors are responsible for the contents of this publication.
PY - 2016/1/6
Y1 - 2016/1/6
N2 - Automated guided vehicles (AGVs) with autonomous behavior and decentralized human–machine interaction (HMI) are suitable for use in logistics. To facilitate natural interaction, HMI may involve both speech and gesture control. This paper presents a new cognitive approach based on electroencephalography (EEG) for multimodal HMI combining speech and gesture control for AGVs used in logistics. The results indicate that implicit EEG-based measures such as alertness and relaxation significantly affect speech control performance. Consequently, monitoring the user's cognitive workload during logistic operations may lead to a substantial improvement in work performance.
AB - Automated guided vehicles (AGVs) with autonomous behavior and decentralized human–machine interaction (HMI) are suitable for use in logistics. To facilitate natural interaction, HMI may involve both speech and gesture control. This paper presents a new cognitive approach based on electroencephalography (EEG) for multimodal HMI combining speech and gesture control for AGVs used in logistics. The results indicate that implicit EEG-based measures such as alertness and relaxation significantly affect speech control performance. Consequently, monitoring the user's cognitive workload during logistic operations may lead to a substantial improvement in work performance.
KW - Cognitive robotics
KW - Electroencephalography
KW - Logistics
UR - http://www.scopus.com/inward/record.url?scp=84973569672&partnerID=8YFLogxK
U2 - 10.1016/j.cirp.2016.04.030
DO - 10.1016/j.cirp.2016.04.030
M3 - Article
AN - SCOPUS:84973569672
VL - 65
SP - 425
EP - 428
JO - CIRP Annals - Manufacturing Technology
JF - CIRP Annals - Manufacturing Technology
SN - 0007-8506
IS - 1
ER -