HAbot: a human-centered augmented reality robot programming method with the awareness of cognitive load.

Area of Science:

• Human-Robot Interaction
• Manufacturing Technology
• Augmented Reality

Background:

• Industry 4.0 adoption of collaborative robots (Cobots) is increasing.
• Existing robot programming methods are complex, requiring extensive expertise.
• Manufacturing faces labor shortages, necessitating intuitive automation solutions.

Purpose of the Study:

• To develop a novel robot programming method for novice users.
• To investigate the impact of cognitive load on human-robot interaction.
• To enhance task completion effectiveness, efficiency, and intuitiveness in Cobot programming.

Main Methods:

• Designed HA$$bot, a human-centered augmented reality programming interface.
• Utilized NASA's system design theory and cognitive load theory for AR-HRI guidelines.
• Implemented a human-in-the-loop workflow with cognitive load management features.
• Validated HA$$bot through user studies involving complex tasks and 16 participants.

Main Results:

• HA$$bot demonstrated higher efficiency compared to existing programming methods.
• Participants experienced lower overall and per-type cognitive loads with HA$$bot.
• The study indicated improved safety when using the HA$$bot interface.
• Quantitative and qualitative data supported HA$$bot's effectiveness.

Conclusions:

• HA$$bot offers an intuitive and effective solution for novice Cobot programming.
• Awareness and management of cognitive load are crucial for successful human-robot collaboration.
• The proposed AR interface significantly improves user experience and task performance in manufacturing settings.