Earthmoving operations with wheel loaders require substantial power and incur high operational costs. This work presents an efficient automation framework based on the Fundamental Earthmoving Equation (FEE) for soil-tool interaction modeling. A reduced-order multi-step parameter estimation method guided by Sobol's global sensitivity analysis is deployed for accurate, online excavation force prediction. An optimal control problem is then formulated to compute energy-efficient bucket trajectories using soil parameters identified in the previous digging cycle. High-fidelity simulations in Algoryx Dynamics confirm accurate force prediction and demonstrate 15-40% energy savings compared to standard paths. The total computation time is comparable to a single digging cycle, highlighting the framework's potential for real-time, energy-optimized wheel loader automation.
Cite
@article{arxiv.2509.10642,
title = {Optimal Path Planning for Wheel Loader Automation Enabled by Efficient Soil-Tool Interaction Modeling},
author = {Armin Abdolmohammadi and Navid Mojahed and Bahram Ravani and Shima Nazari},
journal= {arXiv preprint arXiv:2509.10642},
year = {2025}
}