A robust mobile robot indoor positioning system based on Wi-Fi

被引:15
|
作者
Cui, Wei [1 ]
Liu, Qingde [1 ]
Zhang, Linhan [2 ]
Wang, Haixia [1 ]
Lu, Xiao [1 ]
Li, Junliang [1 ]
机构
[1] Shandong Univ Sci & Technol, Key Lab Robot & Intelligent Technol Shandong Prov, Qingdao 266590, Peoples R China
[2] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin, Peoples R China
基金
中国国家自然科学基金;
关键词
Indoor positioning system; mobile robot; robust principal component analysis; extreme learning machine; EXTREME LEARNING-MACHINE; ALGORITHM; LOCALIZATION; LOCATION; FINGERPRINT; MULTIPATH;
D O I
10.1177/1729881419896660
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Recently, most of the existing mobile robot indoor positioning systems (IPSs) use infrared sensors, cameras, and other extra infrastructures. They usually suffer from high cost and special hardware implementation. In order to address the above problems, this article proposes a Wi-Fi-based indoor mobile robot positioning system and designs and develops a robot positioning platform based on the commercial Wi-Fi devices, such as Wi-Fi routers. Furthermore, a robust principal component analysis-based extreme learning machine algorithm is proposed to address the issue of noisy measurements in IPSs. Real-world robot indoor positioning experiments are extensively carried out and the results verify the effectiveness and superiority of the proposed system.
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页数:10
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