Visual perception and navigation of security robot based on deep learning - 文章详情页

作者：

Li, Xiuzhi (Li, Xiuzhi.) | Guo, Kangkai (Guo, Kangkai.) | Jia, Tong (Jia, Tong.) | Zhang, Xiangyin (Zhang, Xiangyin.)

收录：

EI Scopus

摘要：

This　work　presents　a　vision　based　security　robot　perception　and　control　strategy　for　semi-structured　and　unstructured　roads　navigation.　The　main　contributions　contain　deep　learning　technique　for　road　recognition　and　a　hybrid　navigation　scheme.　A　deep　convolutional　neural　network　is　employed　to　perform　pixel-wise　segmentation　and　thus　to　find　road　regions.　Secondly,　based　on　the　segmented　regions,　an　edge　extraction　algorithm　is　designed　to　extract　and　fit　the　road　boundaries.　To　ensure　the　robustness　of　navigation,　the　region　detection　algorithm　is　proposed　to　ensure　the　robot　to　movement　on　the　traversable　area.　Experimental　results　verify　the　effectiveness　of　proposed　visual　navigation　approaches.　©　2020　IEEE.

关键词：

Roads and streets Navigation Deep neural networks Robots Convolutional neural networks Deep learning Visual servoing

作者机构：

[ 1 ] [Li, Xiuzhi]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
[ 2 ] [Guo, Kangkai]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
[ 3 ] [Jia, Tong]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
[ 4 ] [Zhang, Xiangyin]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China

通讯作者信息：

电子邮件地址：

查看成果更多字段

成果类型
所属机构

所有年份指定年份从至