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cs.RO2025★ 1 cited
Failure-Aware Multi-Robot Coordination for Resilient and Adaptive Target Tracking
Peihan Li, Jiazhen Liu, Yuwei Wu +1
Multi-robot coordination is crucial for autonomous systems, yet real-world deployments often encounter various failures. These include both temporary and permanent disruptions in s…
cs.RO2025★ 1 cited
LLM-Flock: LLM-Driven Decentralized Multi-Robot Flocking via Influence-Based Consensus with Collision Avoidance
Peihan Li, Lifeng Zhou
Large Language Models (LLMs) have shown strong capabilities in reasoning and planning, prompting researchers to explore their use as decentralized decision-makers for multi-robot f…
cs.RO2025
Large Language Models for Multi-Robot Systems: A Survey
Peihan Li, Zijian An, Shams Abrar +1
The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, task allocation and planning, and…