基于离散傅里叶变换的距离多智能体编队容错控制

Hao-Yu Wang
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引用次数: 0

摘要

多智能体编队是一种基于无线传感器网络(WSN)的移动机器人集群,其中每个智能体都具有感知和计算能力。它在交通运输、航空航天、勘探等领域有着广泛的应用。地层控制的主要难点是定位精度和容错性。现有的技术一般是通过距离信息和其他辅助信息相结合来实现的。然而,这些技术在成本和通用性方面都存在局限性,因此对于大型地层系统来说是不可行的。提出了一种仅限距离的多智能体编队容错控制方法。我们使用的主要技术是离散傅里叶变换(DFT)。在圆运动和直线运动相结合的前提下,利用离散时间序列的DFT估计agent的运动参数。在此基础上,通过监测相关目标的关联参考点,编队中的每一个个体都可以在自己的局部坐标系中准确地定位到相邻个体的坐标。在噪声模拟实验中,该方法将地层距离误差降低了20%左右。实验结果也表明了该方法对非刚性地层形状控制的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault-Tolerate Control for Distance-Only Multi-agent Formation Using Discrete Fourier Transform
Multi-agent formation is a mobile robot cluster based on wireless sensor network(WSN), in which each agent has the ability of sensing and computing. It has a wide range of applications in the fields of transportation, aerospace, exploration, etc. The main difficulty of formation control is positioning accuracy and fault tolerance. Existing technology is generally realized by combining distance information and other auxiliary information. However, these technologies have limitations both in cost and generality, so it is infeasible for a large-scale formation system. In this paper, a fault-tolerate formation control method for distance-only multi-agent formation is proposed. The main technique we use is Discrete Fourier Transform (DFT). On the premise of combination in circle and linear motion, the motion parameters of agent are estimated by DFT during discrete time series. On this basis, by monitoring the associated reference points of related targets, each individual in the formation can accurately locate the coordinates of neighbors in its own local coordinate system. In the noise simulation experiment, this method reduces formation distance error by about 20%. The experiment results also show efficiency in non-rigid formation shape control.
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