Yinghao Zhao
Papers
1
Total Citations
12
H-Index
1
About
Yinghao Zhao is a robotics researcher whose work centers on advancing robotic manipulation through vision-guided control, with a particular focus on high-precision assembly tasks. His major contribution lies in developing learning-based frameworks that enable robots to perform sub-millimeter peg-in-hole insertions on unseen object shapes—a notoriously difficult challenge in industrial automation. By drawing inspiration from human visual-motor coordination, Zhao designed architectures that leverage "seam representation"—the visible gap between peg and hole—to estimate both position and orientation for precise pose alignment. His 2022 paper on this approach has garnered 12 citations, establishing a foundation for vision-based, generalizable assembly skills. This work is notable for bridging the gap between simulation and real-world deployment, demonstrating that robots can adapt to novel geometries without task-specific training. Zhao's research has implications for manufacturing, electronics assembly, and any domain requiring delicate, contact-rich manipulation. His approach of mimicking human attention to visual seams offers a promising pathway toward more dexterous and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1