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浙江大学学报(工学版)
J4  2014, Vol. 48 Issue (2): 285-291    DOI: 10.3785/j.issn.1008-973X.2014.02.015
电信技术     
单目视觉自然路标辅助的移动机器人定位方法
陈明芽1,2, 项志宇1,2, 刘济林1,2
1.浙江大学 信息与电子工程系 ,浙江 杭州, 310027；2.浙江省综合信息网重点实验室,浙江 杭州, 310027
Assistance localization method for mobile robot based on
monocular natural visual landmarks
CHEN Ming-ya1,2, XIANG Zhi-yu1,2, LIU Ji-lin1,2
1. Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China;
2. Zhejiang Provincial Key Laboratory of Information Network Technology, Hangzhou 310027, China
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摘要：

针对很多场合下GPS信号会受到遮挡而无法使用,导致机器人定位精度下降很快的问题,提出一种基于单目视觉自然路标辅助的机器人绝对定位方法.在导航环境中的若干位置预先建立视觉路标库.机器人在利用惯导（INS）定位过程中,同时对采集到的单目图像和库中的视觉路标进行匹配.建立基于全局特征信息（GIST）和快速鲁棒算子（SURF）局部特征相结合的在线图像快速匹配框架,同时结合基于单目视觉的运动估计算法修正车体航向.最后利用卡尔曼滤波将视觉路标匹配获得的定位信息和INS有效地融合起来.结果表明，该方法有效地提高在GPS受限情况下惯性导航定位的精度和鲁棒性.
Abstract:

In many occasions GPS signal may be blocked, leading the quick drop of the positioning accuracy for the robot. We present an assistance localization method for mobile robot based on the monocular natural visual landmarks. A landmark library containing the images from several scenes of the environment was set up before navigation. Each acquired image was matched with the visual landmarks while navigation, where INS positioning was used for rough localization. A fast image matching framework based on combining usage of GIST global features and SURF local features was presented. The Orientation was corrected from Structure From Motion algorithm as well. Finally a Kalman Filter was used to fuse the localization results from visual landmarks and the INS method. The results show that the proposed method improves the positioning accuracy under GPS blocked area and makes the system more robust.
出版日期: 2014-02-01
:  TP 242.6  
基金资助:

国家自然科学基金项目（61071219）.
通讯作者: 项志宇，男，副教授.     E-mail: xiangzy@zju.edu.cn
作者简介: 陈明芽（1987—），男，硕士生，从事惯性导航相关研究.E-mail:chenmyzju@gmail.com
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引用本文:

陈明芽, 项志宇, 刘济林. 单目视觉自然路标辅助的移动机器人定位方法[J]. J4, 2014, 48(2): 285-291.

CHEN Ming-ya, XIANG Zhi-yu, LIU Ji-lin. Assistance localization method for mobile robot based on
monocular natural visual landmarks. J4, 2014, 48(2): 285-291.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2014.02.015    或    http://www.zjujournals.com/eng/CN/Y2014/V48/I2/285

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