Papers

4

Total Citations

60

H-Index

2

About

Dr. Yanling Xu is a leading researcher in intelligent robotic welding, with a focus on laser vision-based seam tracking and automation. Her major contributions lie in developing advanced algorithms for autonomous feature point extraction, enabling robots to precisely locate and track weld seams without manual teaching. Her most cited work, the LSFP-Tracker (2023, 39 citations), introduces a Siamese network-based method that significantly improves the flexibility and accuracy of laser stripe feature point extraction for robotic welding. This is complemented by her 2024 study on automatic feature point extraction for multi-layer multi-pass welding (17 citations), which addresses complex industrial scenarios. Dr. Xu’s research extends to 3D point cloud-based localization for teaching-free automation (2025) and thermal analysis of grinding processes for superalloys like Inconel 718 (2019). Her work is pivotal in advancing smart manufacturing, reducing human intervention, and enhancing weld quality. With a growing citation impact, Dr. Xu is recognized for bridging computer vision and robotic welding, making her a key figure in the field of industrial automation.

Research Focus

Key Achievements

2
H-Index
4
Papers
60
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
LSFP-Tracker: An Autonomous Laser Stripe Feature Point Extraction Algorithm Based on Siamese Network for Robotic Welding Seam Tracking
39 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Shanghai Jiao Tong University, China State Shipbuilding (China)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago