AI RESEARCH
Before Humans Join the Team: Diagnosing Coordination Failures in Healthcare Robot Team Simulation
arXiv CS.AI
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ArXi:2508.04691v2 Announce Type: replace-cross As humans move toward collaborating with coordinated robot teams, understanding how these teams coordinate and fail is essential for building trust and ensuring safety. However, exposing human collaborators to coordination failures during early-stage development is costly and risky, particularly in high-stakes domains such as healthcare. We adopt an agent-simulation approach in which all team roles, including the supervisory manager, are instantiated as LLM agents, allowing us to diagnose coordination failures before humans join the team.