Calibrated Dynamic Modeling for Force and Payload Estimation in Hydraulic Machinery

TL;DR

This paper presents a retrofittable, real-time framework for estimating end-effector interaction forces and bucket payloads in hydraulic excavators. By identifying a lightweight, parameterized dynamic model and using both online force-vector estimation and trajectory-wide payload optimization, the approach achieves around 1% full-scale payload accuracy across two machines and provides live force measurements suitable for closed-loop control. It avoids disassembly or machine-specific parameter knowledge, instead using cylinder pressures and kinematic data to calibrate inertia, gravity, friction, and centripetal effects. The results outperform classical quasistatic payload estimators and a commercial system in accuracy and precision, with practical runtimes suitable for embedded deployment on construction-site hardware, enabling more autonomous and safer earthworking tasks.

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.

Figures (15)

• Figure 1: CASE250 excavator used for evaluation. Definition and naming of angles, torques and external force.
• Figure 2: Definition and naming of positions and links in the kinematic setup of the joint.
• Figure 3: Simulated coriolis and gravity-induced torques for a typical digging motion at 0.7EE velocity on M545.
• Figure 4: Up - and down motion. Identification of torque contributing effects on CASE250.
• Figure 5: Boom chamber pressure change for 1EE gravity force over the workspace of the M545 machine. Color shows kinematic sensitivity. The prismatic joint of the M545 remains locked for our experiments.