论文标题
Bflier's:一种新型蝴蝶启发的多发性模型,以搜索信号源
Bflier's: A Novel Butterfly Inspired Multi-robotic Model in Search of Signal Sources
论文作者
论文摘要
自然界中多元化的生态学在许多物种中具有各种形式的群体行为。蝴蝶物种是随机飞行的突出物种之一,有点有见地,并将其转化为人工隐喻将导致巨大的可能性。本文认为一种这种隐喻称为蝴蝶交配优化(BMO)。在BMO中,BFLE遵循巡逻的交配现象,并同时捕获了多模式函数的所有局部优点。为了模仿该算法,设计了一个移动机器人(BFlyBot),以符合BMO算法中BFLE的功能。此外,多Bflybot群的设计旨在像蝴蝶自然界一样行事,并遵循该算法的规则。实时实验是在多动物领域的BMO算法上进行的,并将信号源视为光源。实验结果表明,BMO算法适用于检测多个信号源,其运动的变化显着,即静态和动态。在静态信号源的情况下,随着Bflybot的初始位置的不同,收敛性在时间和平稳性方面受到影响。而具有变化尺寸的实验会导致它们在机器人的执行时间和速度方面变化。在这项工作中,在动态环境中进行了实验,在动态环境中,信号源在操纵和非操作场景中的运动。 Bflybot群能够检测到单个和多信号源,在两个固定点之间在两个固定点之间进行线性移动,以圆形,上下移动。评估BMO现象,讨论了BMO现象,包括中海船舶检测,空中搜索应用,以及地震预测的各种持续和前瞻性工作。
The diversified ecology in nature had various forms of swarm behaviors in many species. The butterfly species is one of the prominent and a bit insightful in their random flights and converting that into an artificial metaphor would lead to enormous possibilities. This paper considers one such metaphor known as Butterfly Mating Optimization (BMO). In BMO, the Bfly follows the patrolling mating phenomena and simultaneously captures all the local optima of multimodal functions. To imitate this algorithm, a mobile robot (Bflybot) was designed to meet the features of the Bfly in the BMO algorithm. Also, the multi-Bflybot swarm is designed to act like butterflies in nature and follow the algorithm's rules. The real-time experiments were performed on the BMO algorithm in the multi-robotic arena and considered the signal source as the light source. The experimental results show that the BMO algorithm is applicable to detect multiple signal sources with significant variations in their movements i.e., static and dynamic. In the case of static signal sources, with varying initial locations of Bflybots, the convergence is affected in terms of time and smoothness. Whereas the experiments with varying step-size leads to their variation in the execution time and speed of the bots. In this work, experiments were performed in a dynamic environment where the movement of the signal source in both maneuvering and non-maneuvering scenarios. The Bflybot swarm is able to detect the single and multi-signal sources, moving linearly in between two fixed points, in circular, up and down movements.To evaluate the BMO phenomenon, various ongoing and prospective works such as mid-sea ship detection, aerial search applications, and earthquake prediction were discussed.