Physics Informed Structural Load Aware Work Path Planning for a Tilt-Rotator Excavator Using Multibody Dynamics and Dueling Deep Q-Learning: A Numerical Case Study

A tilt-rotator increases the reachable workspace of a hydraulic excavator, but its configuration also changes structural load paths. This study developed a structural-load-aware work-path planner for a 14-ton excavator using nominal analytical soil loads and an experimentally correlated multibody dynamics model. A full-factorial combination of five tilt angles, five rotation angles, and nine excavation positions yielded 225 candidate motions. The 147 retained motions had predicted peak stresses of 98.5–149.0 MPa. These stresses informed action features and reward penalties in an action-conditioned dueling deep Q-network. Excavated cells became non-traversable holes; the planner incorporated in-place turning and conditional posture-repeat constraints. In the 9 × 9 obstacle environment, the stress-informed agent’s selected route required 44 actions and 452 s of simulated time, compared with 47 actions and 458 s for its stress-uninformed counterpart; cumulative peak-stress indices were 3158.0 and 3361.8 MPa, respectively. In the 5 × 5 environment, its route required one additional action and had a 4.2% higher index. A 21 × 28 site-derived numerical environment was completed in 453 actions, including 280 excavations. The method supports comparative structural-load assessment for construction-machinery safety and future integration with machine-stability criteria. These single-seed comparisons neither establish statistical superiority nor validate machine stability.