Vision Based Mapping And Localization In Unknown Environment For Intelligent Mobile Robot

被引:0
|
作者
Qiu, Xiaoxin [1 ]
Lu, Hong [2 ]
Zhang, Wenqiang [1 ]
Bai, Yunhan [2 ]
Fu, Qianzhong [1 ]
机构
[1] Fudan Univ, Sch Comp Sci, Shanghai Engn Res Ctr Video Technol & Syst, Shanghai, Peoples R China
[2] Fudan Univ, Sch Comp Sci, Shanghai Key Lab Intelligent Informat Proc, Shanghai, Peoples R China
来源
2014 IEEE 11TH INTL CONF ON UBIQUITOUS INTELLIGENCE AND COMPUTING AND 2014 IEEE 11TH INTL CONF ON AUTONOMIC AND TRUSTED COMPUTING AND 2014 IEEE 14TH INTL CONF ON SCALABLE COMPUTING AND COMMUNICATIONS AND ITS ASSOCIATED WORKSHOPS | 2014年
基金
中国国家自然科学基金;
关键词
SLAM; robot; vision; EKF; mapping;
D O I
10.1109/UIC-ATC-ScalCom.2014.61
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 (SLAM) is a key component of mobile robot's navigation. In this paper, we present a vision-based system of mapping and localization. The system builds a map which contains 3D landmarks of environment. 3D landmarks are reconstructed based on sequential Harris Corner Features. In order to match regained features with landmarks in the map, we present a simple method, i.e. Inverse Projection. The method is relatively simple and effective. We also propose an efficient observe model that simplifies the Jacobian Matrix when apply the Extended Kalman Filter (EKF) framework. We conduct experiments in both simulation and real-time environment, and give error analysis for robot's and landmarks' position. Experiment results show that landmarks are localized accurately and robot trajectory is well estimated by matched landmarks.
引用
收藏
页码:701 / 706
页数:6
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