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PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components with a Robotic Line Scanner
Chen, Hongpeng Huo, Shengzeng Muddassir, Muhammad Lee, Hoi-Yin Liu, Yuli Li, Junxi Duan, Anqing Zheng, Pai Navarro-Alarcon, David
Chen, Hongpeng
Huo, Shengzeng
Muddassir, Muhammad
Lee, Hoi-Yin
Liu, Yuli
Li, Junxi
Duan, Anqing
Zheng, Pai
Navarro-Alarcon, David
Department
Robotics
Embargo End Date
Type
Journal article
Date
2025
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Language
English
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Abstract
The automatic inspection of surface defects is an essential task for quality control in the computers, communications, and consumer electronics (3C) industry. Traditional inspection mechanisms (viz. line-scan sensors) have a limited field of view, 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 paper, 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.
Citation
H. Chen et al., “PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components With a Robotic Line Scanner,” IEEE Trans Instrum Meas, vol. 74, pp. 1–12, 2025, doi: 10.1109/TIM.2025.3552466.
Source
IEEE Transactions on Instrumentation and Measurement
Conference
Keywords
3C components, Coverage path planning (CPP), Line-scan sensor, Robotic inspection, Surface inspection
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Publisher
IEEE