Learning a System-Level Surrogate for Hydraulic Excavators: A Simulation-to-Real LSTM Approach
Developing autonomous hydraulic excavators is constrained by limited access to physical machines and the high cost of real-world experimentation. This paper proposes a simulation-to-real framework for learning a system-level digital surrogate using Long Short-Term Memory (LSTM) networks. Instead of modeling internal dy...