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Agentic AI for Robot Teams

This presentation highlights recent efforts at the Johns Hopkins Applied Physics Laboratory to advance agentic AI for collaborative robotic teams. It begins by framing the core challenges of enabling autonomy, coordination, and adaptability across heterogeneous systems, then introduces a scalable architecture designed to support agentic behaviors in multi-robot environments. The talk concludes with key challenges encountered and practical lessons learned from ongoing research and development.

SourceIEEE Spectrum AIAuthor: Johns Hopkins Applied Physics Laboratory
Agentic AI for Robot Teams
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Key points and analysis

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Key points

  • Introduction to LLM-based AI Agents
  • Approach to applying LLM-based AI Agents to robotic teams
  • Demonstrations with a heterogeneous team of robots in hardware
  • Lessons learned and future work

Highlights and analysis are generated automatically and may contain errors. Check the original source.