Extended Reality for Enhanced Human-Robot Collaboration: a Human-in-the-Loop Approach
This addresses the problem of inflexible automation in manufacturing for industries needing customization, but it appears incremental as it builds on existing human-robot collaboration concepts with XR integration.
The paper tackles the challenge of balancing automation efficiency with flexibility in manufacturing by proposing a human-in-the-loop framework using Extended Reality (XR) to enhance human-robot collaboration, aiming for higher adaptability and task generalization without specifying concrete results or numbers.
The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for customization. Human-robot collaboration attempts to tackle these challenges by combining the strength and precision of machines with human ingenuity and perceptual understanding. In this paper, we conceptualize and propose an implementation framework for an autonomous, machine learning-based manipulator that incorporates human-in-the-loop principles and leverages Extended Reality (XR) to facilitate intuitive communication and programming between humans and robots. Furthermore, the conceptual framework foresees human involvement directly in the robot learning process, resulting in higher adaptability and task generalization. The paper highlights key technologies enabling the proposed framework, emphasizing the importance of developing the digital ecosystem as a whole. Additionally, we review the existent implementation approaches of XR in human-robot collaboration, showcasing diverse perspectives and methodologies. The challenges and future outlooks are discussed, delving into the major obstacles and potential research avenues of XR for more natural human-robot interaction and integration in the industrial landscape.