Innovation and Optimization of VMT Visual System Calibration Method

Abstract

VMT visual localization is a technology that employs cameras for non-contact positioning of workpieces. It is commonly used in high-precision automated sealing workstations for body positioning. The traditional approach to calibrating visual systems has been through online debugging. This method requires using production downtime, has short debugging time windows, long cycles, and incurs high trial-and-error costs. Moreover, the necessary coordinate transformation techniques in visual debugging are often proprietary and require expensive outsourcing due to foreign vendor confidentiality. To address these challenges, this paper proposes two optimizations for visual calibration methods: 1.a novel offline debugging approach to replace the conventional online debugging, reducing the debugging cycle and enhancing efficiency. 2. an innovative coordinate transformation strategy and implementation method, along with a one-click transformation feature implemented through Python code. Lastly, the effectiveness of the proposed methods is demonstrated through application on new vehicle models. This leads to significant cost savings in debugging expenses. The approach has been successfully promoted within the company.