Papers

4

Total Citations

33

H-Index

3

About

Xiaokang Xu is an emerging researcher specializing in industrial robotics, automated manufacturing, and precision calibration, with a particular focus on Automated Fiber Placement (AFP) systems for advanced composite material production. His work addresses one of the most technically demanding challenges in modern aerospace and heavy-industry manufacturing: achieving high positioning accuracy in heavy-duty robotic systems subject to complex mechanical and dynamic loads. Xu's most influential contribution, a 2022 paper accumulating 16 citations, introduced a sophisticated modeling and calibration framework for AFP robots that accounts for compliance and joint-dependent errors — factors critically important when handling the substantial mass of industrial robotic arms during carbon fiber composite lay-up. Subsequent research has expanded this foundation, investigating end-effector contact force estimation under dynamic load variations, multi-source lay-up error analysis, and hydraulic equilibrium dynamics in heavy-duty systems — each garnering recognition within the robotics and manufacturing communities. Collectively, Xu's body of work, totaling over 30 citations across four papers, demonstrates a coherent and deepening research trajectory aimed at making robotic AFP processes more accurate, reliable, and industrially viable — capabilities essential for next-generation lightweight structural manufacturing in aerospace and automotive sectors.

Research Focus

Key Achievements

3
H-Index
4
Papers
33
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
A Modeling and Calibration Method of Heavy-Duty Automated Fiber Placement Robot Considering Compliance and Joint-Dependent Errors
16 citations · 2022
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Zhejiang University of Technology, Zhejiang University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago