Papers
43
Total Citations
914
H-Index
18
About
Xincheng Tian is a prolific researcher whose work sits at the intersection of robotic welding automation, computer vision, and intelligent sensing systems. With a career spanning nearly a decade of high-impact publications, Tian has made significant contributions to advancing the precision and efficiency of industrial robotics, particularly in complex welding applications. His most celebrated work introduces a Two-Stage Industrial Defect Detection Framework combining improved YOLOv5 and Optimized-Inception-ResnetV2 models, garnering 120 citations and addressing longstanding accuracy challenges in industrial quality control. Equally influential is his pioneering research on 3D vision-based robotic welding path planning, with multiple papers tackling the formidable challenge of welding intersecting pipes and complex curved structures — collectively amassing nearly 270 citations. His earlier foundational work on automatic programming for industrial welding robots (2015) helped establish the trajectory of the field. Beyond welding, Tian has expanded into mobile robot orientation determination and MEMS-based joint angle estimation, demonstrating a versatile command of sensor fusion technologies. His cumulative citation count of over 500 underscores his growing influence as a key innovator in intelligent manufacturing and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 3Automatic programming for industrial robot to weld intersecting pipes53 citations · 2015
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