Yuliang Mo
Papers
2
Total Citations
12
H-Index
2
About
Yuliang Mo is a researcher specializing in intelligent robotic welding and cooperative motion control. Their work focuses on advancing automated manufacturing for complex spatial tasks, particularly in welding processes that require precise coordination between robots and external positioners. Mo’s major contributions include the development of a synchronous cooperative path planning (SCPP) algorithm, which enables robots and positioners to collaboratively process complex space curve workpieces—such as intersecting line welds—with enhanced accuracy and efficiency. This work, published in 2020, has garnered 6 citations and addresses critical challenges in industrial automation. More recently, Mo introduced a novel 8-shape trajectory weaving welding control algorithm with auto-adjusting welding torch attitude (2022), also cited 6 times, which improves weld quality by dynamically adapting the torch’s orientation during weaving motions. These innovations demonstrate Mo’s impact on advancing adaptive control and path optimization in robotic welding, offering practical solutions for high-precision manufacturing. Their research is highly relevant for students and engineers exploring cooperative robotics, real-time control systems, and automated welding technologies.
Research Focus
Key Achievements
Top Papers
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