Jiqiang Huang
Papers
6
Total Citations
55
H-Index
4
About
Jiqiang Huang is a leading researcher in intelligent robotic welding systems, with a focus on vision-based automation and mobile welding platforms. His work bridges computer vision and industrial robotics, particularly through laser vision sensing and deep learning. His most cited paper, "A guidance system for robotic welding based on an improved YOLOv5 algorithm with a RealSense depth camera" (2023, 18 citations), introduces a novel approach that replaces manual laser vision sensor guidance with autonomous, real-time workpiece detection, significantly boosting welding robot productivity. Earlier foundational contributions include "Welding deviation detection algorithm based on extremum of molten pool image contour" (2015, 15 citations) and "Study on a Pipe Welding Robot based on Laser Vision Sensing" (2008, 9 citations), which pioneered two-dimensional groove recognition and tracking for pipe welding. Huang also advanced adaptive control with "Constant speed control for complex cross-section welding using robot based on angle self-test" (2014, 8 citations). More recently, his reviews and experiments on mobile welding robots for expandable convoluted pipes (2025) address critical challenges in unstructured field environments, such as confined spaces and irregular shapes. With a career spanning foundational sensing techniques to modern AI-driven automation, Huang’s work directly impacts productivity and autonomy in construction, pipeline, and bridge welding.
Research Focus
Key Achievements
Top Papers
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- 3Study on a Pipe Welding Robot based on Laser Vision Sensing9 citations · 2008
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- 5Mobile welding robots under special working conditions: a review3 citations · 2025
- 6