This paper describes the creation and assessment of a stereo vision-based 3D reconstruction system that integrates the UR5 robotic arm with the Solomon 3D camera. The technology aims to increase the accuracy and efficiency of 3D object modeling in industrial automation situations. To handle the special difficulties presented by stereo vision in real-time 3D data processing and object manipulation, the Iterative Closest Point (ICP) technique is applied and enhanced to improve the system's capacity to engage interactively with recognized objects and improve spatial accuracy. The outcomes of the experiments demonstrate notable progress in terms of both speed and accuracy for 3D reconstruction, which is a major improvement over conventional stereovision techniques. This study emphasizes the potential of combining advanced stereovision technology with robotic arms to optimize industrial processes, presenting a step forward in the automation of complex tasks.