HA $$R^{2}$$ R 2 bot: a human-centered augmented reality robot programming method with the awareness of cognitive load

Wenhao Yang, Qinqin Xiao and Yunbo Zhang ()
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Wenhao Yang: Rochester Institute of Technology
Qinqin Xiao: University of Rochester
Yunbo Zhang: Rochester Institute of Technology

Journal of Intelligent Manufacturing, 2024, vol. 35, issue 5, No 6, 1985-2003

Abstract: 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 HA $$R^{2}$$ R 2 bot, 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 HA $$R^{2}$$ R 2 bot are verified in two complex tasks compared with existing online programming methods. We also evaluated HA $$R^{2}$$ R 2 bot quantitatively and qualitatively through a user study with 16 participants. According to the user study, compared with existing methods, HA $$R^{2}$$ R 2 bot has higher efficiency, a lower overall cognitive load, lower cognitive loads for each type, and higher safety.

Keywords: Augmented reality; Human–robot interaction; Collaborative robot; Cognitive load (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10845-023-02096-2

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