Title :
Estimation and tracking of excavated material in mining
Author :
Innes, Christopher ; Nettleton, Eric ; Melkumyan, Arman
Author_Institution :
Australian Center for Field Robot., Univ. of Sydney, Sydney, NSW, Australia
Abstract :
This paper provides a method for representing, tracking and fusing information on excavated material as it moves through a mining process chain. A constrained augmented state Kalman filter (based on simultaneous localization and mapping principles) is used as the basis for this process. A method for representing the material properties stochastically based on the unique location of the lumped material is also developed. Through the application of this method, correlations between material at different locations can be maintained. This method is validated through real world experiments simulating an open pit mine excavation.
Keywords :
Kalman filters; materials properties; mining industry; sensor fusion; stochastic processes; target tracking; constrained augmented state Kalman filter; excavated material tracking; information fusion; lumped material; mining industry; mining process chain; open pit mine excavation; Correlation; Covariance matrix; Equations; Kalman filters; Material properties; Mathematical model; Data association; Estimation; Kalman filtering; Tracking;
Conference_Titel :
Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4577-0267-9
