Papers
4
Total Citations
110
H-Index
4
About
Yanqin Ma is a leading researcher in intelligent robotic assembly, with a focus on precision manipulation for small-scale components. Her work bridges computer vision, force sensing, and machine learning to enable robots to perform complex assembly tasks with human-like dexterity. Ma’s most cited paper, “Robotic grasping and alignment for small size components assembly based on visual servoing” (2020, 45 citations), established a foundational method for real-time visual feedback in micro-assembly. She further advanced the field with her 2019 work on an automatic precision robot assembly system integrating microscopic vision and force sensors (32 citations), demonstrating a complete industrial solution. Notably, her 2022 paper on an efficient skill learning framework (23 citations) introduced a novel approach requiring only a few demonstrations, significantly reducing the data burden for training assembly networks. Ma’s contributions have been instrumental in making robotic assembly more adaptive and accessible, with applications in electronics manufacturing and micro-device production. Her work continues to shape the future of automated precision manufacturing.
Research Focus
Key Achievements
Top Papers
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- 4Automatic grasping control of mobile robot based on monocular vision10 citations · 2022