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LLMs integrated into multi-robot systems, with benchmarks for edge devices

By PulseAugur Editorial · [3 sources] ·

A survey paper reviews the integration of Large Language Models (LLMs) into Multi-Robot Systems (MRS), categorizing applications from high-level task allocation to low-level action generation. It highlights challenges such as mathematical reasoning limitations and hallucination, while also outlining future research opportunities in fine-tuning and reasoning techniques. Separately, another paper benchmarks 25 open-source language models for deployment on edge devices in social robots, evaluating inference efficiency, general knowledge, and teaching effectiveness. AI

IMPACT Explores LLM integration in robotics for enhanced coordination and efficiency, and benchmarks models for edge deployment in social robots.

RANK_REASON The cluster contains two academic papers discussing the application and benchmarking of language models in robotics.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

LLMs integrated into multi-robot systems, with benchmarks for edge devices

COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · Peihan Li, Zijian An, Shams Abrar, Lifeng Zhou ·

    Large Language Models for Multi-Robot Systems: A Survey

    arXiv:2502.03814v5 Announce Type: replace-cross Abstract: 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 human-robot interaction. Unlike traditiona…

  2. arXiv cs.CL TIER_1 English(EN) · Dorian Lamouille, Matev\v{z} B. Zorec, Farnaz Baksh, Karl Kruusam\"ae ·

    Benchmarking Local Language Models for Social Robots using Edge Devices

    arXiv:2605.03111v1 Announce Type: cross Abstract: Social-educational robots designed for socially interactive pedagogical support, such as the Robot Study Companion (RSC), rely on responsive, privacy-preserving interaction despite severely limited compute. However, there is a gap…

  3. arXiv cs.CL TIER_1 English(EN) · Karl Kruusamäe ·

    Benchmarking Local Language Models for Social Robots using Edge Devices

    Social-educational robots designed for socially interactive pedagogical support, such as the Robot Study Companion (RSC), rely on responsive, privacy-preserving interaction despite severely limited compute. However, there is a gap in systematic benchmarking of language models for…

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