YuKang Liu
Papers
12
Total Citations
375
H-Index
7
About
YuKang Liu is a pioneering researcher at the intersection of robotics, artificial intelligence, and advanced manufacturing, with a particular focus on intelligent welding systems and human-robot knowledge transfer. His work addresses one of manufacturing's most persistent challenges: capturing and replicating the nuanced expertise of skilled human welders within automated robotic systems. Liu's most influential contribution, "Dynamic Neuro-Fuzzy-Based Human Intelligence Modeling and Control in GTAW" (2013, 104 citations), established a landmark framework for encoding human welder cognition into neuro-fuzzy controllers, enabling automated Gas Tungsten Arc Welding systems to replicate expert decision-making in real time. Building on this foundation, his 2014 paper on remotely controlled welding robots (89 citations) introduced an innovative teleoperation architecture using a 6-DOF robotic arm equipped with 3D weld pool sensing, effectively bridging human intuition and machine execution. His 2015 work on supervised learning of welder behaviors (64 citations) further advanced this vision by demonstrating machine learning's capacity to transfer skilled human responses directly to robotic platforms. Collectively accumulating over 370 citations, Liu's research has meaningfully advanced intelligent manufacturing, offering transformative pathways toward adaptive, self-learning welding robots capable of matching human craftsmanship.
Research Focus
Key Achievements
Top Papers
- 1Dynamic Neuro-Fuzzy-Based Human Intelligence Modeling and Control in GTAW104 citations · 2013
- 2Toward Welding Robot With Human Knowledge: A Remotely-Controlled Approach89 citations · 2014
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- 6Predictive control for robot arm teleoperation14 citations · 2013
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- 8Dynamic Control of 3D Weld Pool Surface Based on Human Response Model6 citations · 2014
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