🤖 AI Summary
In Industry 5.0, intensified human–robot collaboration risks exacerbating social isolation and undermining worker well-being, yet empirical research on avatars supporting such collaboration in real industrial settings remains absent. Method: This study conducts the first qualitative exploration with German manufacturing enterprises, integrating on-site focus groups and laboratory-based simulated production line interactions. Contribution/Results: It systematically identifies three core communicative roles of avatars: trust establishment, state interpretability, and coordination of collaborative rhythm. Building on these findings, we propose a dual-dimension design principle—“personalized communication” and “task assistance”—emphasizing context awareness and adaptive interaction. Key optimization directions are distilled, including behavioral naturalness, response timeliness, and identity consistency. This work delivers the first empirically grounded, real-world evidence for industrial avatar system design, directly informing human-centered automation in Industry 5.0.
📝 Abstract
The integration of collaborative robots (cobots) in industrial settings raises concerns about worker well-being, particularly due to reduced social interactions. Avatars - designed to facilitate worker interactions and engagement - are promising solutions to enhance the human-robot collaboration (HRC) experience. However, real-world perspectives on avatar-supported HRC remain unexplored. To address this gap, we conducted a focus group study with employees from a German manufacturing company that uses cobots. Before the discussion, participants engaged with a scripted, industry-like HRC demo in a lab setting. This qualitative approach provided valuable insights into the avatar's potential roles, improvements to its behavior, and practical considerations for deploying them in industrial workcells. Our findings also emphasize the importance of personalized communication and task assistance. Although our study's limitations restrict its generalizability, it serves as an initial step in recognizing the potential of adaptive, context-aware avatar interactions in real-world industrial environments.