Solving Source Location Problems with Particle Swarm Optimizer and Height Information

Junqi Zhang, Yehao Lu, Mengchu Zhou
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Abstract

Recently, there has been great interest in utilizing robot swarm to solve source location problems. A particle swarm optimizer (PSO) is among the most popular method. To our best knowledge, almost all work in this field focuses on a 2-D search space while ignoring height information. This work proposes a 3-D source location model where the sensing range of an unmanned aerial vehicle (UAV) gradually increases with its flying height, but its obtained signal strength gradually weakens. It can avoid meaningless wandering of UAV s in no-signal areas. Experimental results show that the effective use of height information can significantly improve the search efficiency.
利用粒子群优化器和高度信息求解源定位问题
近年来,利用机器人群来解决源定位问题引起了人们的极大兴趣。粒子群优化算法(PSO)是其中最常用的一种方法。据我们所知,该领域几乎所有的工作都集中在二维搜索空间,而忽略了高度信息。本文提出了一种三维源定位模型,其中无人机的传感距离随着飞行高度的增加而逐渐增大,但其获得的信号强度逐渐减弱。它可以避免无人机在无信号区域无意义的徘徊。实验结果表明,有效利用高度信息可以显著提高搜索效率。
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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