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机器人群的自我组织神经系统

Weixu Zhu¹, Sinan Oğuz^1,2, Mary Katherine Heinrich¹

¹IRIDIA, Université Libre de Bruxelles, Brussels, Belgium.

Science robotics

|November 13, 2024

概括

我们介绍了自组织神经系统 (SoNS),一种新的机器人群架构. 这种方法可以实现自主重新配置和本地协调,在可扩展性,灵活性和容错性方面推进群体机器人能力.

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
复杂的系统复杂的系统.

背景情况:

群体机器人通常依赖于去中心化的控制.
现有的架构经常在动态重新配置和局部协调方面扎.
可扩展性,灵活性和容错性是群系统中的关键挑战.

研究的目的:

引入自我组织神经系统 (SoNS) 作为一种新的机器人群架构.
展示动态多层次层次结构的自主建立,维护和重新配置.
以局部集中的方式展示协调的传感,执行和决策.

主要方法:

基于自我组织的层次结构的SoNS架构的开发.
为机器人群落实施动态的多层系统架构.
使用异构的空中地面机器人群的概念验证任务.
基于物理的模拟用于可扩展性测试 (最多250个机器人).

主要成果:

机器人群体的自主转化为具有动态层次的单个或多个SoNS.
传感,执行和决策的成功协调.
在二元决策和搜救等任务中推进最先进的群体机器人能力.
在模拟和现实实验中证明了可扩展性和容错性.

结论:

SoNS方法使机器人能够自主创建和管理复杂的动态层次结构.
它实现了本地集中,而不会影响诸如可扩展性和容错等群体优势.
SoNS显著提高了群体机器人的能力和适用性.

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