精度稀释
计算机科学
航向(导航)
扩展卡尔曼滤波器
基线(sea)
卡尔曼滤波器
实时计算
多向性
超宽带
定位系统
移动机器人
机器人
职位(财务)
人工智能
节点(物理)
全球定位系统
电信
工程类
全球导航卫星系统应用
海洋学
结构工程
财务
地质学
经济
航空航天工程
作者
Sy-Hung Bach,Phan Bùi Khôi,Soo-Yeong Yi
出处
期刊:IEEE Internet of Things Journal
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-1
标识
DOI:10.1109/jiot.2024.3354786
摘要
Autonomous mobile robots (AMRs) play a crucial role in smart factories and Internet of Things (IoT) applications. This paper presents a high-accuracy localization system called the global UWB system (GUS) for the AMR based on ultra-wideband (UWB) distance measurements. By using two UWB modules (tags) on AMR, it is possible to estimate both position and heading angle simultaneously, which can solve the problem of error accumulation over time in internal sensors. A new tightly coupled algorithm called baseline constraint extended Kalman filter (BC-EKF) is proposed. The baseline is the actual distance between the two tags that is used as a constraint for the measurement process. The relationship between the baseline and the heading angle error is also discussed to ensure reasonable deployment of the tags. The proposed localization method is persistent as value of the geometric dilution of precision (GDOP) increases. This helps to secure the performance of the localization method even in tight workspaces where the number of fixed UWBs (anchors) is limited. The simulation and experiment results demonstrate the localization performance of the proposed method.
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