Flocking Model for Self-Organized Swarms

Kevin Marlon Soza Mamani, Fabio Richard Diaz Palacios
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Abstract

The algorithms of self-organized swarm control refer first to two basic behaviors, these are aggregation and flocking. The present work focuses its research on coordinated movement behavior that is defined as the ability of a group of individuals (usually composed of hundreds or thousands) to move and maneuver in a coordinated manner as if they were a single structure. Such behavior refers us to studies carried out in the field of trajectory control and aggregation behavior, both being keys for the development of a coordinated movement control algorithm. Therefore, control of the system starts from the combination of these studies. The control is a leading robot model which can be designated for any unit according to the assigned task. On the other hand, all robots except the leader keep the group attached and keeping a safe distance. The simulations of the system were developed for three units and later for twelve, observing the cohesion and uniformity of the swarm in movement.
自组织群体的群集模型
自组织群体控制算法首先涉及两种基本行为,即聚集和群集。目前的工作重点是研究协调运动行为,它被定义为一群个体(通常由数百或数千人组成)以协调的方式移动和机动的能力,就好像他们是一个单一的结构。这种行为是指在轨迹控制和聚集行为领域进行的研究,这两者都是开发协调运动控制算法的关键。因此,系统的控制从这些研究的结合开始。该控制器是一个领先的机器人模型,可以根据分配的任务为任何单元指定。另一方面,除了leader,所有的机器人都保持着群体的联系和安全距离。该系统的模拟发展为三个单位,后来为十二个,观察群体的凝聚力和均匀性在运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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