Verifier-Mediated Multi-LLM Coordination for Multi-Robot Path Planning

Key points

• Foundation models are increasingly used for high-level multi-robot task planning, yet independently generated symbolic plans can become jointly infeasible after geometric grounding because of shared spatial and temporal constraints.1
• We compare a centralized architecture, in which one LLM jointly reasons over the robot team, with a decentralized multi-LLM architecture in which each robot independently proposes a task plan.1
• This verifier-mediated architecture separates semantic task reasoning from execution-level feasibility while enabling iterative coordination among LLM planners.1
• Experiments in CARLA and on Crazyflie aerial robots evaluate coordination performance as task complexity increases and characterize the trade-offs between centralized reasoning, decentralized verifier-mediated coordination, and physical executability.1

Sources (1)

• [1]Verifier-Mediated Multi-LLM Coordination for Multi-Robot Path Planning
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 10:12 PM

  We study execution-aware coordination of large-language-model (LLM) planners for multi-robot navigation.

  Foundation models are increasingly used for high-level multi-robot task planning, yet independently generated symbolic plans can become jointly infeasible after geometric grounding because of shared spatial and temporal constraints.

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