Sensor Fusion of INS, Odometer and GPS for Robot Localization

被引：0
|
作者：
Yousuf, Sofia [1 ]
Kadri, Muhammad Bilal [1 ]
机构：
[1] Karachi Inst Econ & Technol PAF KIET, Coll Engn, Karachi, Pakistan
来源：
2016 IEEE CONFERENCE ON SYSTEMS, PROCESS AND CONTROL (ICSPC) | 2016年
关键词：
Kalman Filter; GPS; sensor fusion; Inertial Navigation System (INS);
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 presents data fusion of three sensors Inertial Navigation System (INS), Global positioning systems (GPS) and odometer for determining the correct location of a differential drive mobile robot. The data from INS and odometer is combined using Kalman Filter (KF) based sensor fusion technique. The KF filtered signal and the GPS signal is fused by assigning weights. The proposed technique is tested in simulation. Mathematical models of the three sensors as well as the robot model is developed in MATLAB/Simulink environment to generate the data for simulation purpose. It has been demonstrated that with the proposed sensor fusion architecture exact geo-location of a differential drive wheeled robot can be determined to a greater degree of accuracy in an indoor or outdoor environment.
引用
收藏
页码：118 / 123
页数：6
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