Yingwu He
Papers
3
Total Citations
18
H-Index
2
About
Yingwu He is a robotics researcher whose work focuses on enhancing the safety, precision, and coordination of robotic systems in industrial and human-robot collaboration settings. His primary research areas include collision detection, motion planning, and kinematic calibration for robotic manipulators and parallel robots. He is best known for developing a collision detection method that uses time-series analysis to sense external forces without requiring external sensors—a critical innovation for safe human-robot interaction. This work, published in 2020, has garnered 13 citations, reflecting its growing influence in the field. He has also contributed to coordinated motion planning for manipulator-positioner systems, enabling complex tasks like welding and polishing on curved surfaces, and proposed an efficient accuracy calibration method for translational parallel robots that reduces measurement complexity by using only a subset of error data. These contributions demonstrate his commitment to practical, cost-effective solutions that improve robot autonomy and reliability. His research is particularly valuable for advancing collaborative robotics in manufacturing, where safety and precision are paramount.
Research Focus
Key Achievements
Top Papers
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