An Approach for Estimation of Swing Angle and Digging Depth During Excavation Operation

Abstract

This paper discusses the estimation of the swing angle and digging depth during the excavation operation. The ability to calculate the excavator's productivity is an essential step toward autonomous excavators. The swing angle and digging depth have significant effects on the excavator's productivity and must be taken into account for the productivity estimation. Two approaches are proposed to estimate these variables. The first method estimates the swing angle using cabin encoder measurements. The local minimum and maximum points are found, and then Otsu's method is exploited to detect the points that are representative of scooping and dumping positions. The second method utilizes the bucket position to estimate the digging depth. The bucket position is calculated using Inertial Measurement Units (IMUs) measurements and the forward kinematics of the excavator. Otsu's method is used to distinguish the local minimum points that are representative of the digging depth during the operation. Moreover, the algorithms are computationally efficient. Finally, the performance of the proposed methods is studied using real measurements. The results show that the methods can effectively estimate the swing angle and digging depth under different working c onditions s uch a s various materials, swing angles, and digging depths.

Automatic Estimation of Excavator’s Actual Productivity in Trenching and Grading Operations Using Building Information Modeling (BIM)

“…The worksite managers can modify the number of resources and machines in a site based on productivity to ensure the project stays on schedule and within budget. Additionally, human operators can improve their skills by employing the machine's productivity [3,4].…”