PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components With a Robotic Line Scanner

The automatic inspection of surface defects is an essential task for quality control in the computers, communications, and consumer (3C) electronics industry. Traditional inspection mechanisms (i.e., line-scan sensors) have a limited field of view (FOV), thus prompting the necessity for a multifaceted robotic inspection system capable of comprehensive scanning. Optimally selecting the robot’s viewpoints and planning a path is regarded as coverage path planning (CPP), a problem that enables inspecting the object’s complete surface while reducing the scanning time and avoiding misdetection of defects. In this article, we present a new approach for robotic line scanners to detect surface defects of 3C free-form objects automatically. A two-stage region segmentation method defines the local scanning based on the random sample consensus (RANSAC) and K-means clustering to improve the inspection coverage. The proposed method also consists of an adaptive region-of-interest (ROI) algorithm to define the local scanning paths. Besides, a particle swarm optimization (PSO)-based method is used for global inspection path generation to minimize the inspection time. The developed method is validated by simulation-based and experimental studies on various free-form workpieces, and its performance is compared with that of two state-of-the-art solutions. The reported results demonstrate the feasibility and effectiveness of our proposed method.

I. Introduction

Defect inspection is essential to quality control, process monitoring, and nondestructive testing (NDT) in the manufacturing industry [1], [2]. Specifically, manufacturing processes in the computers, communications, and consumer (3C) industry are highly sophisticated and demand detailed and accurate defect inspection. Traditional defect inspection approaches typically rely on visual inspection of an intermediate/finished product by a quality control or quality check inspector. This sole dependence on human workers is a problem for regions and countries with a shortage of manpower [3], [4], [5]. Furthermore, human-based inspection is inherently subjective and, hence, prone to errors. To address these issues, various researchers have reported the automatic surface inspection system for free-form components [6], [7].