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Aggregation of heterogeneous units in a swarm of robotic agents

机译:一群机器人药剂中异质单位的聚集

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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.
机译:异质类型的相互作用单元中的模式形成图案是在许多生物系统中看到的自组织行为。该区域的早期研究表明,由于不同类型的细胞或组织之间的粘附性差异,可以使生物细胞和组织中的这种模式形成行为进行。受到这种差动粘合性模型的启发,在我们之前的研究中,我们介绍了一种基于差异人工潜力的分散方法,以实现群中的异质机器人群中的分离行为,其中不同类型的不同类型的特异性分离的簇。在本文中,我们通过提出一种方法来实现这种方法来实现不同类型的代理彼此均匀混合的聚集。该方法基于不同类型的代理在与不同类型的代理相互作用的同时经历不同类型的代理体验变化的电位量。利用Lyapunov Sense中提出的方法的分析进行了稳定性。广泛的仿真研究和数值分析表明,该方法将导致非均相药物群体以聚集配置。

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