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生物代理视觉通信的概念:将群体智能与生物同类联系起来

Bryan Starbuck¹, Hanlong Li¹, Bryan Cochran¹

¹George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Biomimetics (Basel, Switzerland)

|September 26, 2025

概括

这项研究将生物通信策略转化为无人机 (UAV) 群体在无射频环境中的视觉信号. 基于运动的信号传输被证明是非常有效的清晰和富有表现力的去中心化通信.

科学领域:

机器人技术机器人技术机器人技术
人工智能的人工智能
生物启发工程生物启发工程

背景情况:

生物群体表现出去中心化,适应性通信,这对于没有中央控制的协调至关重要.
现有的无人飞行器 (UAV) 通信系统在无线电频率被拒绝的环境中面临限制.

研究的目的:

开发一种生物灵感的视觉通信系统,用于无人机群体在无线电频率被拒绝的环境中运行.
将生物通信原则转化为无人机代理的生成视觉语言.
评估生物代理通信在保护和调整信号含义方面的有效性.

主要方法:

构建了一个配置空间,通过轨迹和LED图案编码视觉信息,灵感来自自然动物信号 (例如,蜜蜂摇摆舞,鹿标志).
使用大型语言模型 (LLM) 与检索增强生成 (RAG) 来解释感知数据并生成象征性UAV响应.
通过五个测试案例评估系统,评估模式内忠实性和跨模式转换,使用共变性和自值分解分析.

主要成果:

基于运动的信号显示了近乎完美的清晰度 (0.992) 和表现力 (1,000),表明高度有效的分散通信.
只有LED和多信号通信实现了高表达力 (~1000),但清晰度明显降低 (≤0.298).
生物代理方法支持清晰,富有表现力和分散的沟通.

结论:

生物通信原则可以有效地转化为UAV群体的视觉语言.
基于运动的视觉信号提供了一个强大的解决方案,用于在具有挑战性的无射频环境中实现分散通信.
需要进一步的研究来优化多模式信号,以提高清晰度和表达力.

关键词:

代理人工智能的人工智能生物启发的沟通是生物启发的沟通.生成型的人工智能大型语言模型多代理系统是多代理系统.提取-增强生成的回收.无人驾驶飞行器成群结队而来.

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