Transforming Monolithic Foundation Models into Embodied Multi-Agent Architectures for Human-Robot Collaboration

Understand

Foundation models have become central to unifying perception and planning in robotics, yet real-world deployment exposes a mismatch between their monolithic assumption that a single model can handle all cognitive functions and the distributed, dynamic nature of practical service workflows.

• Vision-language models offer strong semantic understanding but lack embodiment-aware action capabilities while relying on hand-crafted skills.
• Vision-Language-Action policies enable reactive manipulation but remain brittle across embodiments, weak in geometric grounding, and devoid of proactive collaboration mechanisms.
• These limitations indicate that scaling a single model alone cannot deliver reliable autonomy for service robots operating in human-populated settings.