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The automation of the excavation process has a huge potential in many industries that require earth removal. The online estimation of soil parameters is an important requirement for developing an impedance controller architecture for automated excavation strategies. This paper presents a fast and robust technique for the experimental identification of soil. This technique, based on the Newton-Raphson method, estimates the unknown parameters of the soil mechanics equations by minimizing the error between measured failure forces and estimated failure forces. The measured failure forces can be obtained by measuring the forces acting on the bucket during the excavation operation, while the estimated failure forces are obtained by an analytical soil model. The Mohr-Coulomb soil model and the Chen and Liu upper bound soil model are employed in this soil parameter estimation scheme. The proposed estimation method is compared to the parameter space intersection method previously employed for parameter estimation and has been tested using four different types of soils (Ticino, Rained Ticino, Nevada Fine, and Glass Beads). The results show that the proposed technique is in good agreement with the parameter space intersection method, but outperforms the latter in terms of computational execution time. A further disadvantage of the parameter space intersection method is that it relies on the search space to be stored in a tabular form. Hence, if high accuracy is needed, the discretization step of the tabular data has to be very small, leading to high memory requirements. Further, in contrast to the method proposed here, the parameter space intersection method suffers from the curse of dimensionality, which leads to exorbitant memory requirements when searching in high-dimensional parameter spaces. The presented results show that the proposed technique has high robustness to initial condition variations and is very insensitive to perturbations of the input signal. The technique - presented in this paper is generic and suitable for a real-time soil parameter estimation scheme.