A Feature Matching Method For Simultaneous Localization And Mapping

被引：0

作者：

Chen Xiangkui ^{[1
,2
]}

Jiang Min ^{[1
,2
]}

Zuo Liangyu ^{[1
]}

Jiang Jian ^{[1
]}

机构：

[1] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan, Hubei, Peoples R China

[2] Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan, Hubei, Peoples R China

来源：

PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC) | 2017年

基金：

中国国家自然科学基金;

关键词：

Simultaneous Localization and Mapping; Feature Matching; SIFT; FREAK;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Simultaneous Localization and Mapping is an important technology which help a mobile robot to determine its location and build the environment map. Recently, the RGBD sensor is widely used in the robot, research on RGBD-SLAM becomes a hot topic. In order to calculate the movement parameters of robot, feature matching is adopted to register the two adjacent RGBD images in the video stream. This paper proposed an improved feature matching method for RGBD-SLAM. The experiment results show that, compared with the traditional SIFT feature matching methods for RGBD-SLAM, the performance of the proposed method is improved significantly.

引用

页码：1091 / 1094

页数：4

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