Abstract
The high traffic in the container yard requires effective management, and one method to address this is through automation. The Rubber Tyred Gantry Crane (RTGC) plays a crucial role in container yards. Automating the RTGC involves determining the container’s location and sway angle to provide feedback for the control system. The advancements in computer vision technology offer a unique solution to tackle these challenges. This paper proposes image processing as a means to sense the sway angle and MobileNet SSD to detect the container’s location. The proposed method yields accurate measurement results and is integrated with optimized PID-PD for position and sway angle control in RTGC. The effectiveness of the proposed method is demonstrated through successful performance in both simulation and experiments conducted on a laboratory-scale RTGC prototype.
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