机器人代理群中异质单元的集合

Manish Kumar, D. Garg
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引用次数: 3

摘要

在异质类型的相互作用单元系统中,模式的形成是一种自组织行为,在许多生物系统中都可以看到。该领域的早期研究表明,不同类型的细胞或组织之间的黏附性不同,使得生物细胞和组织中的这种模式形成行为成为可能。受这种差异粘附模型的启发,在我们早期的研究中,我们提出了一种基于差异人工势的分散方法来实现异质机器人智能体群体中的隔离行为,其中不同类型的智能体形成空间分离的集群。在本文中,我们扩展了这项工作,提出了一种实现聚合的方法,其中不同类型的代理彼此均匀混合。该方法基于一个命题,即不同类型的智能体在与不同类型的智能体相互作用时,会经历不同幅度的电位。在李亚普诺夫意义下对系统进行了稳定性分析。广泛的模拟研究和数值分析表明,所提出的方法将导致异质代理群体的聚合配置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aggregation of heterogeneous units in a swarm of robotic agents
Formation of patterns in a system of interacting units of heterogeneous types is a self-organized behavior which is seen in many biological systems. Earlier research in this area has indicated that such pattern formation behaviors in biological cells and tissues are made possible because of difference in the adhesivity between different types of cells or tissues. Inspired by this differential adhesivity model, in our earlier research, we had presented a decentralized approach based on differential artificial potential to achieve the segregation behavior in a swarm of heterogeneous robotic agents in which agents of different types formed spatially separate clusters. In this paper, we extend that work by presenting an approach to achieve aggregation in which agents of different types get uniformly mixed with each other. The method is based on the proposition that agents of different types experience varying magnitude of potential while interacting with the agents of different types. An analysis of the system with the proposed approach in Lyapunov sense is carried out for stability. Extensive simulation studies and numerical analysis suggest that the proposed method would lead a population of heterogeneous agents to an aggregated configuration.
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