mlsanityData to 14 Oct 2026

From Virtual Agents to Robot Teams: A Multi-Robot Framework Evaluation in High-Stakes Healthcare Context

arXiv 2506.03546 ↗First posted 4 Jun 2025cs.RO cs.AI cs.MAcited by 3

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Abstract (arXiv)

Advancements in generative models have enabled multi-agent systems (MAS) to perform complex virtual tasks such as writing and code generation, which do not generalize well to physical multi-agent robotic teams. Current frameworks often treat agents as conceptual task executors rather than physically embodied entities, and overlook critical real-world constraints such as spatial context, robotic capabilities (e.g., sensing and navigation). To probe this gap, we reconfigure and stress-test a hierarchical multi-agent robotic team built on the CrewAI framework in a simulated emergency department onboarding scenario. We identify five persistent failure modes: role misalignment; tool access violations; lack of in-time handling of failure reports; noncompliance with prescribed workflows; bypassing or false reporting of task completion. Based on this analysis, we propose three design guidelines emphasizing process transparency, proactive failure recovery, and contextual grounding. Our work informs the development of more resilient and robust multi-agent robotic systems (MARS), including opportunities to extend virtual multi-agent frameworks to the real world.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 30 of its 66 references that are in the map. First posted on arXiv 4 Jun 2025.

Builds on

30 of 66 references.

References · 30

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18 more
  1. 2025Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systemscited by 185
  2. 2023RoCo: Dialectic Multi-Robot Collaboration with Large Language Modelscited by 172
  3. 2024LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Aheadcited by 155
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directionscited by 48
  2. 2026Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypescited by 2
  3. 2025Large Language Models and 3D Vision for Intelligent Robotic Perception and Autonomycited by 0