Bucket trajectory classification of mining excavators

Large mining excavators impose numerous challenges to the operator during a dig. A semi-automated or fully automated machine that could assist the operator during excavation would positively affect efficiency, ore selectivity, and reduce machine wear at the same time. Besides, the dependence on operator skills and attentiveness will be reduced. In order to realize any control on an excavator, it is prudent to know the dig patterns followed by the operator during a real time dig. This paper aims to classify the dig by analyzing the actual task performed by the operator. The trajectories are classified based on the location and angle of the bucket. Both 2-dimensional and 3-dimensional analyses of the bucket trajectory were performed on a EX 3500 mining excavator at the Newmont open pit mine using Arial Performance Analysis System (APAS).