Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/76130
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Type: Conference paper
Title: A simulation study of sensor data fusion using UKF for bucket wheel reclaimer localization
Author: Zhao, S.
Lu, T.
Koch, B.
Hurdsman, A.
Citation: Proceedings of the 8th IEEE International Conference on Automation Science and Engineering, held in Seoul, Korea, 20-24 August, 2012: pp.1192-1197
Publisher: IEEE
Publisher Place: USA
Issue Date: 2012
ISBN: 9781467304290
ISSN: 2161-8070
2161-8089
Conference Name: IEEE International Conference on Automation Science and Engineering (8th : 2012 : Seoul, Korea)
Statement of
Responsibility: 
Shi Zhao, Tien-Fu Lu, Ben Koch and Alan Hurdsman
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: Australia
global positioning system
marine vehicles
measurement uncertainty
noise
resistance
silicon compounds
Rights: © Copyright 2012 IEEE - All rights reserved.
DOI: 10.1109/CoASE.2012.6386509
Published version: http://dx.doi.org/10.1109/coase.2012.6386509
Appears in Collections:Aurora harvest
Mechanical Engineering conference papers

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