Yukang Liu
Papers
3
Total Citations
45
H-Index
2
About
Yukang Liu is a leading researcher at the intersection of intelligent manufacturing and robotic welding, with a primary focus on modeling, real-time prediction, and human-robot collaboration in complex welding processes. His most impactful work, “Modeling and real-time prediction for complex welding process based on weld pool” (2018, 38 citations), introduces innovative methods to analyze and predict weld pool behavior in real time, a critical step toward autonomous, high-quality welding. Liu’s research uniquely bridges human welder expertise and robotic precision, as demonstrated in his studies on 3-D hand movement learning in virtualized gas tungsten arc welding (GTAW). His doctoral dissertation, “Virtualized Welding Based Learning of Human Welder Behaviors for Intelligent Robotic Welding” (2014), lays the foundation for next-generation intelligent welding systems that combine human sensing and adaptability with robotic consistency and accuracy. By developing process modeling and control methods that learn from skilled welders, Liu has advanced the field of intelligent manufacturing, enabling more adaptive, efficient, and reliable automated welding solutions. His work is essential reading for researchers and engineers aiming to build truly intelligent robotic systems for complex industrial applications.
Research Focus
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Top Papers
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