On-line soil property estimation for autonomous excavator vehicles

This paper presents a novel method for estimating soil properties on-line during excavation tasks such as ground leveling, digging and sheet pilling. The proposed method computes key soil parameters by measuring the forces acting on the excavator bucket whilst being in contact with the soil and minimizing the error between measured forces and estimated forces produced by a real-time capable soil model. Two soil models, the Mohr-Coulomb soil model and the Chen and Liu upper bound soil model, are implemented and researched in the context of this estimation scheme. Parameter optimization is carried out employing the Newton Raphson method. The method is evaluated using experimental data and through comparison with an approach that makes use of graphical intersection for model optimization. The results demonstrate that the proposed Newton Raphson-based method is as accurate as the graphical intersection-based approach, but up to 2000 times faster, and thus, most suitable for on-line soil parameter estimation in an automated system which provides optimized digging trajectories for a given excavation task.