Calibrated Dynamic Modeling for Force and Payload Estimation in Hydraulic Machinery

Abstract

Accurate real-time estimation of end effector interaction forces in hydraulic excavators is a key enabler for advanced automation in heavy machinery. Accurate knowledge of these forces allows improved, precise grading and digging maneuvers. To address these challenges, we introduce a high-accuracy, retrofittable 2D force- and payload estimation algorithm that does not impose additional requirements on the operator regarding trajectory, acceleration or the use of the slew joint. The approach is designed for retrofittability, requires minimal calibration and no prior knowledge of machine-specific dynamic characteristics. Specifically, we propose a method for identifying a dynamic model, necessary to estimate both end effector interaction forces and bucket payload during normal operation. Our optimization-based payload estimation achieves a full-scale payload accuracy of 1%. On a standard 25 t excavator, the online force measurement from pressure and inertial measurements achieves a direction accuracy of 13 degree and a magnitude accuracy of 383 N. The method's accuracy and generalization capability are validated on two excavator platforms of different type and weight classes. We benchmark our payload estimation against a classical quasistatic method and a commercially available system. Our system outperforms both in accuracy and precision.