标题:Mobile Robot Indoor Positioning System Based on K-ELM
作者:Wang, Haixia; Li, Junliang; Cui, Wei; Lu, Xiao; Zhang, Zhiguo; Sheng, Chunyang; Liu, Qingde
作者机构:[Wang, Haixia; Li, Junliang; Cui, Wei; Lu, Xiao; Zhang, Zhiguo; Sheng, Chunyang; Liu, Qingde] Shandong Univ Sci & Technol, Key Lab Robot & Intelligent 更多
通讯作者:Cui, Wei;Cui, W
通讯作者地址:[Cui, W]Shandong Univ Sci & Technol, Key Lab Robot & Intelligent Technol Shandong Prov, Qingdao 266590, Peoples R China.
来源:JOURNAL OF SENSORS
出版年:2019
卷:2019
DOI:10.1155/2019/7547648
摘要:Mobile Robot Indoor Positioning System has wide application in the industry and home automation field. Unfortunately, existing mobile robot indoor positioning methods often suffer from poor positioning accuracy, system instability, and need for extra installation efforts. In this paper, we propose a novel positioning system which applies the centralized positioning method into the mobile robot, in which real-time positioning is achieved via interactions between ARM and computer. We apply the Kernel extreme learning machine (K-ELM) algorithm as our positioning algorithm after comparing four different algorithms in simulation experiments. Real-world indoor localization experiments are conducted, and the results demonstrate that the proposed system can not only improve positioning accuracy but also greatly reduce the installation efforts since our system solely relies on Wi-Fi devices.
收录类别:EI;SCIE
资源类型:期刊论文
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