Abstract
In the era of Industry 4.0, manufacturing enterprises are actively adopting collaborative robots (Cobots) in their productions. Current online and offline robot programming methods are difficult to use and require extensive experience or skills. On the other hand, the manufacturing industries are experiencing a labor shortage. An essential question, therefore, is: how would a new robot programming method help novice users complete complex tasks effectively, efficiently, and intuitively? To answer this question, we proposed HAR2bot, a novel human-centered augmented reality programming interface with awareness of cognitive load. Using NASA's system design theory and the cognitive load theory, a set of guidelines for designing an AR-based human-robot interaction system is obtained through a human-centered design process. Based on these guidelines, we designed and implemented a human-in-the-loop workflow with features for cognitive load management. The effectiveness and efficiency of HAR2bot are verified in two complex tasks compared with existing online programming methods. We also evaluated HAR2bot quantitatively and qualitatively through a user study with 16 participants. According to the user study, compared with existing methods, HAR2bot has higher efficiency, a lower overall cognitive load, lower cognitive loads for each type, and higher safety.