Papers
44
Total Citations
948
H-Index
15
About
Zize Liang is a prominent robotics and computer vision researcher whose work spans intelligent welding automation, power line inspection robotics, and advanced sensing technologies. Based at a leading Chinese research institution, Liang has made substantial contributions to transforming industrial robots from rigid, preprogrammed systems into adaptive, perception-driven machines capable of operating in complex real-world environments. Liang's most impactful work focuses on arc welding robotics, where he pioneered novel approaches to 3D seam extraction and path planning using structured light sensors and point cloud segmentation — his 2020 paper on this topic has garnered 193 citations, reflecting its significant influence on the field. His earlier studies on stereo structured light sensing (88 citations) and welding quality detection via 3D reconstruction (78 citations) established a robust foundation for vision-guided welding automation. Beyond welding, Liang has driven innovation in power infrastructure inspection, developing hybrid aerial-climbing robots (69 citations) and deep learning-based detection methods for transmission towers and power lines. His cable-driven snake-like manipulator design further demonstrates his breadth across robotic mechanism innovation. Collectively, Liang's research portfolio — exceeding 668 citations — reflects a consistent commitment to bridging advanced perception technologies with practical industrial robotics applications.
Research Focus
Key Achievements
Top Papers
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- 4Development of a power line inspection robot with hybrid operation modes69 citations · 2017
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