EMOS introduces a revolutionary operating system that enables diverse robot teams to collaborate effectively through LLM-powered agents that understand physical robot capabilities.

• Creates embodiment-aware agents that recognize each robot's physical limitations
• Leverages large language models to coordinate complex multi-robot tasks
• Implements a unified framework for heterogeneous robots to work together seamlessly
• Addresses key challenges in physical robot collaboration unlike software-only multi-agent systems

This research offers significant potential for manufacturing and industrial automation by enabling diverse robots to collaborate on complex tasks that single robots cannot handle alone.

EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents