Virtual Simulation and Experiment of Quality Inspection Robot Workstation

Abstract

(1) Background: Quality inspection robots are widely used in automated production lines. However, the design cycle is long, iteration costs are high, and algorithm development is challenging. It is difficult to perform effective validation during the design phase. Applying virtual reality technology to simulate quality inspection robot workstations offers a new approach to addressing the issues. (2) Methods: The research creates a simulation platform for quality inspection robot workstations based on a virtual reality architecture. The platform creates an immersive quality inspection robot workstation operation interface and conducts testing of the inspection process, thereby validating the rationality of the quality inspection robot workstation design. Building upon this foundation, we conducted experimental comparisons of various defect detection algorithms. (3) Results: Compared to the traditional YOLOv7 algorithm, the improved YOLOv7 algorithm achieved an 18.1% increase in recognition precision. Experimental results demonstrate that the quality inspection robot workstation simulation platform can be applied to validating workstation design proposals. (4) Conclusions: It has a positive impact on reducing the research and development costs of quality inspection robot workstations and shortening the defect recognition algorithm development cycle.