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
Link To Document :
بازگشت