State estimation and vehicle localization for the FIDO rover

被引：16

作者：

Baumgartner, ET ^{[1
]}

Aghazarian, H ^{[1
]}

Trebi-Ollennu, A ^{[1
]}

Huntsberger, TL ^{[1
]}

Garrett, MS ^{[1
]}

机构：

[1] CALTECH, Jet Prop Lab, Sci & Technol Dev Sect, Pasadena, CA 91109 USA

来源：

SENSOR FUSION AND DECENTRALIZED CONTROL IN ROBOTIC SYSTEMS III | 2000年 / 4196卷

关键词：

rover localization; state estimation; extended Kalman filter; covariance intersection;

D O I：

10.1117/12.403731

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

This paper describes the means for generating rover localization information for NASA/JPL's FIDO rover. This is accomplished using a sensor fusion framework which combines wheel odometry with sun sensor and inertial navigation sensors to provide an integrated state estimate for the vehicle's position and orientation relative to a fixed reference frame. This paper describes two separate state estimation approaches built around the extended Kalman filter formulation and the Covariance Intersection formulation. Experimental results from runs in JPL's MarsYard are presented in order to compare the state estimates generated using each formulation.

引用

页码：329 / 336

页数：8

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