Real-Time Volume Estimation of a Dragline Payload
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 realtime. 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％.
Alex Bewley Rajiv Shekhar Sam Leonard Ben Upcroft Paul Lever
University of Queensland,St Lucia Qld,4067 Australia
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
1571-1576
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）