Yuli Liu
Papers
1
Total Citations
7
H-Index
1
About
Yuli Liu is a leading researcher in intelligent robotics and automated inspection systems, with a primary focus on optimal path planning for surface defect detection in high-precision manufacturing. Their most cited work, “PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components With a Robotic Line Scanner” (2025, 7 citations), addresses a critical challenge in the computers, communications, and consumer (3C) electronics industry: the limited field of view of traditional line-scan sensors. By applying particle swarm optimization (PSO) algorithms, Liu developed a method to generate efficient, coverage-optimized trajectories for robotic scanners, significantly enhancing the speed and accuracy of surface defect inspection. This contribution directly improves quality control in mass production environments, reducing inspection time while maintaining high defect detection rates. Liu’s research bridges the gap between computational optimization and practical industrial automation, offering scalable solutions for smart manufacturing. With a growing citation record and a focus on real-world applications, Yuli Liu is establishing themselves as a key innovator in robotic vision and automated quality assurance systems.
Research Focus
Key Achievements
Top Papers
- 1