Optimization of skew angle of the spreader in sea-to-shore gantry cranes

Ports in the world are rated based on the number of containers they handle per year. With this reference, every port is desired to have a huge record of container handling (TEU). Sea-to-shore gantry cranes are critical assets in modern container terminals where productivity, safety and reliability directly affect port performance. One of the persistent operational challenges during container handling is the skew of the spreader relative to the container and ship cell guides, caused by either wind disturbances, trolley motions, wire rope length variations and symmetrical loading. This manuscript presents a vision-based system of spreader skew angles using cameras and intelligent algorithms. The proposed approach integrates malti-camera perception, real-time image processing and control of algorithms to estimate the skew angle accuratelyand apply corrective actions automatically. The system design emphasizes robustiness, real-time performance and compatibility with STS crane control architecture. Simulation and conceptual validation demonstrate that the proposed system can significantly reduce skewing during hoisting ad positioning, contributing to safer and more efficient container handling operations.