This paper describes an analytical model along with a visualizing tool, based on the error propagation theory to quantify and visualize the uncertainty that is present in the position and pose of the excavator obtained from sensor-based measurements regardless of the type of sensors used. A technique is also presented to aid in the selection process of sensors (precision level) for tracking the excavator (pose and position) considering the tradeoff between the level of precision required in field operation on a specific task and the cost of sensors. A conceptual demonstration of field operation at a grading project is also given at the end; detailed workface level planning is made for a self-tracking excavator equipped with multiple sensors to track its bucket position.
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