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A Robotics Inspection System for Detecting Defects on Semi-specular Painted Automotive Surfaces

Sohail Akhtar, Adarsh Tandiya, Medhat Moussa, Cole Tarry

Year
2020
Citations
7

Abstract

This paper describes the design and implementation of a real-time robotics system for semi-specular/painted surface defect detection. The system can be used on moving parts, tolerate varying lighting conditions, and can accommodate small inherent vibrations of the inspected surface that is common in manufacturing operations. Topographical information of the inspected surface is first obtained by the analysis of reflections of a known pattern from this surface. Spectral analysis is then applied to identify defects through novelty detection. Finally, a defect tracking mechanism eliminates spurious defects. The proposed system operates continuously at 90 fps. The paper presents field testing results that show the system can be used as a consistent and cost-effective way of quality control.

Keywords

Specular reflectionArtificial intelligenceComputer visionRoboticsComputer scienceSurface (topology)Automotive industryMachine visionAutomated optical inspectionRobot

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