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基于LED光色度和频率分量分析的二维定位室内模糊逻辑自主导航系统的数值分析

Numerical Analysis of 2-D Positioned, Indoor, Fuzzy-Logic, Autonomous Navigation System Based on Chromaticity and Frequency-Component Analysis of LED Light.

作者信息

Jeong Jae-Hoon, Park Kiwon

机构信息

The School of IT, Information and Control Engineering, Kunsan National University, Gunsan-si 54150, Korea.

School of Mechanical and Automotive Engineering, Youngsan University, Yangsan-si 50510, Korea.

出版信息

Sensors (Basel). 2021 Jun 25;21(13):4345. doi: 10.3390/s21134345.

Abstract

Topics concerning autonomous navigation, especially those related to positioning systems, have recently attracted increased research attention. The commonly available global positioning system (GPS) is unable to determine the positions of vehicles in GPS-shaded regions. To address this concern, this paper presents a fuzzy-logic system capable of determining the position of a moving robot in a GPS-shaded indoor environment by analyzing the chromaticity and frequency-component ratio of LED lights installed under the ceiling. The proposed system's performance was analyzed by performing a MATLAB simulation of an indoor environment with obstacles. During the simulation, the mobile robot utilized a fuzzy autonomous navigation system with behavioral rules to approach targets successfully in a variety of indoor environments without colliding with obstacles. The robot utilized the x and y coordinates of the fuzzy positioning system. The results obtained in this study confirm the suitability of the proposed method for use in applications involving autonomous navigation of vehicles in areas with poor GPS-signal reception, such as in tunnels.

摘要

与自主导航相关的主题,尤其是那些与定位系统有关的主题,近来已吸引了越来越多的研究关注。常用的全球定位系统(GPS)无法在GPS信号遮挡区域确定车辆的位置。为解决这一问题,本文提出了一种模糊逻辑系统,该系统能够通过分析安装在天花板下方的LED灯的色度和频率分量比,来确定处于GPS信号遮挡的室内环境中移动机器人的位置。通过对具有障碍物的室内环境进行MATLAB模拟,分析了所提出系统的性能。在模拟过程中,移动机器人利用具有行为规则的模糊自主导航系统,在各种室内环境中成功接近目标且不与障碍物碰撞。该机器人利用了模糊定位系统的x和y坐标。本研究获得的结果证实了所提出的方法适用于在GPS信号接收较差的区域(如隧道)中涉及车辆自主导航的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6346/8271869/11c8fbd59263/sensors-21-04345-g001.jpg

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