PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components with a Robotic Line Scanner
arxiv(2023)
摘要
The automatic inspection of surface defects is an important task for quality
control in the computers, communications, and consumer electronics (3C)
industry. Conventional devices for defect inspection (viz. line-scan sensors)
have a limited field of view, thus, a robot-aided defect inspection system
needs to scan the object from multiple viewpoints. 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. However, the
development of CPP strategies for robotic line scanners has not been
sufficiently studied by researchers. To fill this gap in the literature, in
this paper, we present a new approach for robotic line scanners to detect
surface defects of 3C free-form objects automatically. Our proposed solution
consists of generating a local path by a new hybrid region segmentation method
and an adaptive planning algorithm to ensure the coverage of the complete
object surface. An optimization method for the global path sequence is
developed to maximize the scanning efficiency. To verify our proposed
methodology, we conduct detailed simulation-based and experimental studies on
various free-form workpieces, and compare its performance with a
state-of-the-art solution. The reported results demonstrate the feasibility and
effectiveness of our approach.
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