Target location detection of mobile robots based on R-FCN deep convolutional neural network

被引:9
作者
Cen, Hua [1 ]
机构
[1] Guangxi Modern Polytech Coll, Dept Mech & Elect Engn, Hechi 547000, Peoples R China
关键词
R-FCN deep convolutional neural network; Mobile robot; Target location; Intelligent algorithm; TRACKING;
D O I
10.1007/s13198-021-01514-z
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In order to improve the target location detection effect of mobile robots, this paper combines convolutional neural network and recurrent neural network to construct a model for solving abnormal sound event detection. Moreover, this paper constructs a convolutional neural network architecture suitable for feature extraction of audio signals, uses the recurrent neural network to classify each frame of audio signals, and applies the improved R-FCN deep convolutional neural network to the target location detection of mobile robots. In addition, this article uses Matlab to carry out system simulation construction, and design and use the system to carry out performance verification. Through experimental research, it can be seen that the target location system of mobile robot based on R-FCN deep convolutional neural network constructed in this paper can effectively improve the location speed and location accuracy compared with traditional location systems.
引用
收藏
页码:728 / 737
页数:10
相关论文
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[21]   Fuzzy-based Path Planning for Multiple Mobile Robots in Unknown Dynamic Environment [J].
Zhao, Ran ;
Lee, Hong-Kyu .
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2017, 12 (02) :918-925