Papers
4
Total Citations
78
H-Index
3
About
Yukai Chen is a researcher whose work spans industrial robotics, computer vision, and control systems, with a particular focus on advancing automation technologies for real-world manufacturing environments. His most significant contributions lie in the domain of robotic bin picking, where he has developed multi-view image acquisition pipelines combined with CAD-based and model-based pose estimation techniques to enable robots to accurately identify and grasp randomly oriented workpieces. His 2020 paper on this topic has garnered 50 citations, reflecting its strong influence on the robotics and industrial automation community, while his earlier 2018 work laid important groundwork with 17 citations. Beyond perception and manipulation, Chen has extended his research into robust control theory, proposing a disturbance observer-based prescribed-time tracking control scheme for robotic manipulators that handles real-world uncertainties and external disturbances. Notably, his interests also bridge engineering and education: his 2015 study on integrative STEM curriculum design applied project-based learning principles within a robotics summer camp setting, demonstrating a commitment to inspiring the next generation of engineers. Collectively, Chen's research offers meaningful advances across robotic perception, control, and STEM pedagogy.
Research Focus
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