DocumentCode
2603783
Title
A simulation study of sensor data fusion using UKF for bucket wheel reclaimer localization
Author
Zhao, Shi ; Lu, Tien-Fu ; Koch, Ben ; Hurdsman, Alan
Author_Institution
Sch. of Mech. Eng., Univ. of Adelaide, Adelaide, SA, Australia
fYear
2012
fDate
20-24 Aug. 2012
Firstpage
1192
Lastpage
1197
Abstract
Bucket Wheel Reclaimers (BWRs) normally travel on a rail among stockpiles to perform stacking and reclaiming operations. Currently, the position accuracy of the bucket wheel at the end of boom measured by the onboard encoder system is limited to 30cm. To maintain such accuracy, calibrated points have to be placed along the rail, which is inefficient and costly. This paper proposes a simulation study using Unscented Kalman Filter (UKF) algorithm to fuse DGPS and encoder data for BWR localization. The results obtained indicate that the errors in positional accuracy are better than 15cm and UKF is an objective technology that can be applied to localize such large scaled machine.
Keywords
Kalman filters; conveyors; position control; sensor fusion; BWR localization; DGPS; UKF algorithm; bucket wheel reclaimer localization; onboard encoder system; position accuracy; reclaiming operation; sensor data fusion; stacking operation; unscented Kalman filter; Australia; Global Positioning System; Marine vehicles; Measurement uncertainty; Noise; Resistance; Silicon compounds;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Science and Engineering (CASE), 2012 IEEE International Conference on
Conference_Location
Seoul
ISSN
2161-8070
Print_ISBN
978-1-4673-0429-0
Type
conf
DOI
10.1109/CoASE.2012.6386509
Filename
6386509
Link To Document