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High pressure environments (e.g., disaster response) can result in variable workload that decreases human performance, and degrades the overall mission performance of human-robot teams. Preemptive human workload prediction enables the robot to adapt its behavior or the mission plan as a means of optimizing human performance. However, state-of-the-art workload prediction research only predicts cognitive workload for only a maximum of five seconds into the future. An approach for addressing this research gap is to employ multi-step prediction in additional workload components (e.g., cognitive, auditory, speech, visual, gross motor, fine motor, tactile).
Giolando et al. (Mon,) studied this question.