Xiangmiao Wu

South China University of Technology

Papers

10

Total Citations

77

H-Index

5

About

Xiangmiao Wu is a robotics and computer vision researcher whose work sits at the intersection of intelligent welding automation, 3D reconstruction, and robot perception. Wu's research is primarily focused on advancing humanoid welding robots—both terrestrial and underwater—through sophisticated vision systems, artificial intelligence, and path planning algorithms. A standout contribution is Wu's systematic development of 3D point cloud-based reconstruction methods tailored to challenging environments, including low-light underwater welding scenes, achieving high-quality spatial mapping with low latency. Wu's most-cited work, a 2024 systematic review on 3D vision measurement and path planning for humanoid welding robots (24 citations), has quickly established itself as a foundational reference in next-generation intelligent manufacturing. Complementing this, Wu has produced influential reviews and original research on AI-driven underwater welding robots, addressing the dual hardware and software challenges these systems face. Additional contributions include novel calibration frameworks, motion planning algorithms, and real-time arc blow estimation models. Wu's growing citation record—accumulating over 75 citations across publications from 2023 to 2025—reflects rapid recognition within the robotics and advanced manufacturing communities, positioning Wu as an emerging authority in intelligent welding robot systems.

Research Focus

Key Achievements

5
H-Index
10
Papers
77
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Towards new-generation of intelligent welding manufacturing: A systematic review on 3D vision measurement and path planning of humanoid welding robots
24 citations · 2024
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: South China University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago