Abstract
Human attention processes play a key role in optimizations of human-robot collaboration (HRC) systems. We describe a novel framework to assess the human state primarily by gaze and in real-time by deriving parameters about situation awareness which is fundamental in the evaluation of collaboration. Comprehensive experiments on HRC were conducted with typical tasks including collaborative pick-and-place in a lab based prototypical manufacturing environment. The methodology measures executive functions and situation awareness in the HRC task in real-time for the purpose of human factors-based performance evaluation in HRC applications.
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