Multimodal speech and gesture control of AGVs, including EEG-based measurements of cognitive workload

摘要

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. (C) 2016 CIRP.