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|Title:||A simulation study of sensor data fusion using UKF for bucket wheel reclaimer localization|
|Citation:||Proceedings of the 8th IEEE International Conference on Automation Science and Engineering, held in Seoul, Korea, 20-24 August, 2012: pp.1192-1197|
|Conference Name:||IEEE International Conference on Automation Science and Engineering (8th : 2012 : Seoul, Korea)|
|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.|
|Appears in Collections:||Mechanical Engineering conference papers|
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