Robotisation of Mobile Cranes in Walking Operations: Path Planning, and Load Sway Prediction

This thesis advances the automation of mobile crane walking operations with suspended payloads on unstructured construction sites. It presents a comparative study of path planning algorithms across undercarriage configurations, a physics-informed neural network for load sway prediction, and a terrain-adaptive motion planner with sway suppression for uneven terrain and dynamic obstacles. These contributions address the coupling between undercarriage locomotion, suspended payload dynamics, and unstructured terrain, bringing mobile cranes closer to autonomy on construction sites.