Stability analysis of a visual system for docking and positioning of single-column steel tube towers

This paper presents a novel automatic docking and positioning vision system specifically designed for single-column steel towers. It delves into the intricate factors that contribute to the precision of workpiece positioning. The prime objective of this system is to precisely ascertain the position and rotational orientation of the docking port in the assembly of single-column steel pipe towers, ensuring seamless and accurate docking operations. Two webcams constitute the fundamental elements of the system. The proposed algorithm encompasses diverse image processing methodologies, ensuring the attainment of the desired recognition accuracy. To authenticate the recognition quality of the vision system, synthetic images were utilized under a range of conditions, allowing for a thorough analysis of the correlation between the object detection rate and accuracy, and the dimensions of the clipping frame. Experimental findings reveal that the integration of this vision algorithm with a webcam offers a viable alternative to costly industrial vision systems. The two main components of this vision system for automatic docking and positioning of single-column steel pipe towers are the machine vision component for recognition and the vision system component for position estimation.