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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bewley, A. Shekhar, R. Leonard, S. Upcroft, B. Lever, P. |
| Copyright Year | 2011 |
| Description | Author affiliation: University of Queensland, St Lucia, 4067 Australia (Bewley, A.; Shekhar, R.; Leonard, S.; Upcroft, B.; Lever, P.) |
| Abstract | This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%. |
| Starting Page | 1571 |
| Ending Page | 1576 |
| File Size | 1341618 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781612843865 |
| ISSN | 10504729 |
| e-ISBN | 9781612843858 |
| DOI | 10.1109/ICRA.2011.5979898 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-05-09 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Payloads Estimation Three dimensional displays Iterative closest point algorithm Data models Production Laser modes |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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