Zhiqi Wang
Papers
3
Total Citations
106
H-Index
3
About
Dr. Zhiqi Wang is a leading researcher in intelligent robotic machining, whose work bridges structural optimization, sensor fusion, and process control. His core contributions lie in enhancing the precision and adaptability of industrial robots by addressing the often-overlooked interplay between robot flexibility, mounting base stiffness, and machining dynamics. In his highly cited 2024 work (60 citations), Dr. Wang introduced a novel homogeneous stiffness domain index to simultaneously optimize robot base position and spacecraft cabin angles, accounting for nonlinear stiffness characteristics—a breakthrough for large-scale aerospace assembly. He further advanced the field with a mutual cross-attention fusion network (39 citations in 2025), which integrates internal robot signals with external sensor data to predict surface roughness during robotic machining, enabling real-time quality control. Most recently, his spectral clustering-guided multi-objective optimization framework (7 citations) tackles the complex challenge of pose optimization under structural and base flexibility. By systematically modeling and optimizing these coupled variables, Dr. Wang’s research provides a robust theoretical foundation for achieving high-precision, adaptive robotic manufacturing in demanding aerospace applications.
Research Focus
Key Achievements
Top Papers
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