DocumentCode
1862572
Title
Vehicle localization in outdoor woodland environments with sensor fault detection
Author
Morales, Yoichi ; Takeuchi, Eijiro ; Tsubouchi, Takashi
Author_Institution
Grad. Sch. of Syst. & Inf. Eng., Univ. of Tsukuba, Tsukuba
fYear
2008
fDate
19-23 May 2008
Firstpage
449
Lastpage
454
Abstract
This paper describes a 2D localization method for a differential drive mobile vehicle on real forested paths. The mobile vehicle is equipped with two rotary encoders, Crossbow´s NAV420CA inertial measurement unit (IMU) and a NAVCOM SF-2050M GPS receiver (used in StarFire-DGPS dual mode). Loosely-coupled multisensor fusion and sensor fault detection issues are discussed as well. An extended Kalman filter (EKF) is used for sensor fusion estimation where a GPS noise pre-filter is used to avoid introducing biased GPS data (affected by multi-path). Normalized innovation squared (NIS) tests are performed when a GPS measurement is incorporated to reject GPS data outliers and keep the consistency of the filter. Finally, experimental results show the performance of the localization system compared to a previously measured ground truth.
Keywords
Global Positioning System; Kalman filters; mobile robots; nonlinear filters; sensor fusion; 2D localization method; NAVCOM SF-2050M GPS receiver; differential drive mobile vehicle; extended Kalman filter; inertial measurement unit; loosely-coupled multisensor fusion; normalized innovation squared tests; outdoor woodland environments; sensor fault detection; vehicle localization; Fault detection; Filters; Global Positioning System; Navigation; Remotely operated vehicles; Robustness; Sensor fusion; Sensor systems; Testing; Vehicle driving;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on
Conference_Location
Pasadena, CA
ISSN
1050-4729
Print_ISBN
978-1-4244-1646-2
Electronic_ISBN
1050-4729
Type
conf
DOI
10.1109/ROBOT.2008.4543248
Filename
4543248
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