A Navigation System Based on Vision and Motion Fusion Information Using Two UFKs

被引：0

作者：

Yan, Chunming ^{[1
]}

Luo, Jun ^{[1
]}

Pu, Huayan ^{[1
]}

Xie, Shaorong ^{[1
]}

Gu, Jason ^{[2
]}

机构：

[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 20072, Peoples R China

[2] Dalhousie Univ, Dept Elect & Comp Engn, Halifax, NS B3J 2X4, Canada

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION | 2015年

关键词：

robotic navigation; multi-sensor fusion; Kalman filter; UKF;

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：

This paper proposes an autonomous navigation system for mobile robots using two unscented Kalman filters (UKFs) and a slip detector to fuse the vision and motion information. The vision information is extracted from images captured by cameras, while the motion data are gathered by two wheel encoders, an accelerometer and a gyroscope. Firstly, the description of navigation algorithm, including the system overview, the image processing procedure and the coordinate transformation, are presented. Then kinematic models of two UKFs and data integration are introduced. Analyzing the results of experiments, the multi-sensor fusion system has more stability and accuracy in comparison with the single sensor system.

引用

页码：174 / 178

页数：5

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