Xiuqin Shang
Papers
4
Total Citations
12
H-Index
2
About
Xiuqin Shang is a robotics and automation researcher whose work bridges intelligent control, industrial inspection, and 3D perception. Her research centers on developing adaptive robotic systems for manufacturing, with key contributions in two-wheel self-balancing robots, point cloud segmentation, and automated quality inspection. Her early work on a stepper motor-based control system for two-wheel self-balanced robots (2013, 6 citations) simplified traditional designs by eliminating expensive sensors like optical encoders, making such systems more accessible. More recently, she has tackled domain adaptation challenges in industrial point cloud primitive segmentation (2024, 3 citations), proposing a multi-confidence guided method that helps robots recognize geometric shapes across different datasets. Shang also designed a flexible quality inspection robot system for multi-type surface defects (2021, 2 citations), enabling automated detection adaptable to various objects. Her latest work introduces a human-like observation-inspired universal image acquisition system for complex industrial surfaces (2025, 1 citation), mimicking human visual strategies to improve inspection accuracy. Through these contributions, Shang advances practical, cost-effective solutions for industrial automation, demonstrating how robotics can enhance manufacturing quality and efficiency.
Research Focus
Key Achievements
Top Papers
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