How to plan robot paths with limited communication?
Heuristic Planner for Communication-Constrained Multi-Agent Multi-Goal Path Planning
December 19, 2024
https://arxiv.org/pdf/2412.13719This paper tackles the problem of coordinating multiple robots to visit a sequence of goals in an environment with obstacles and limited communication range. The goal is to minimize the total time taken while ensuring the robots remain within communication distance of each other.
Key points for LLM-based multi-agent systems:
- Decentralized coordination: Although the proposed algorithm is centralized, the communication constraints and distributed nature of the problem are highly relevant to LLM agents interacting in a shared environment.
- Resource limitations: The communication constraint highlights the importance of efficient communication strategies in multi-agent LLM systems, particularly when dealing with bandwidth or latency limitations.
- Dynamic planning: The algorithm's epoch-based approach, where plans are adapted based on the current state, reflects the need for dynamic planning and replanning in LLM-based multi-agent systems, especially when dealing with unforeseen events or changing goals.
- Heuristic search: The use of heuristic search in this paper underscores the potential of combining classical AI techniques with LLMs for complex multi-agent coordination tasks. LLMs could be used to generate initial plans or learn heuristics to guide the search.
- Composite state space: The paper's analysis of the challenges of composite state space search highlights the scalability issues inherent in coordinating multiple agents, which are also relevant to LLM-based systems.