Exploring human-robot cooperation with gamified user training: a user study on cooperative lifting

Area of Science:

• Robotics and Human-Computer Interaction
• Industrial Automation and Human Factors

Background:

• Collaborative robots (cobots) are increasingly used in industry, but applications often involve sequential tasks rather than active cooperation.
• Human-robot cooperation (HRC) presents opportunities for enhanced industrial processes, yet effective and rapid user training remains a challenge.

Purpose of the Study:

• To investigate the learnability of a cooperative lifting task (co-lift) with a collaborative robot within a limited timeframe.
• To assess the impact of user background factors on the learning process in HRC tasks.
• To evaluate a gamified training system for HRC skill acquisition.

Main Methods:

• An experimental study involving 32 adults performing a gamified co-lift task with a cobot.
• Utilized Inertial Measurement Unit (IMU) sensors to capture human motion and gestures for robot interaction.
• Explored three role distributions: human-led, robot-led, and shared leadership.

Main Results:

• All users demonstrated satisfactory learning progression, achieving successful cooperation within seven or fewer trials, irrespective of age, gender, or prior experience.
• The gamified training system proved effective for diverse user groups.
• Preliminary data suggests certain user background factors may influence learning outcomes, warranting further investigation.

Conclusions:

• Human-robot cooperation in industrial settings is feasible and promising for a wide range of users, even with minimal training.
• Gamified training methodologies can accelerate skill acquisition for collaborative robot tasks.
• Future research will delve deeper into the influence of user-specific factors on HRC performance.