Yangcheng Wei
Papers
1
Total Citations
4
H-Index
1
About
Yangcheng Wei is a researcher at the forefront of intelligent manufacturing and human-robot interaction, with a primary focus on integrating deep learning and 3D perception into industrial robotic control systems. His most-cited work, "Research of robotic arm control system based on deep learning and 3D point cloud target detection algorithm" (2022), addresses the critical challenge of enabling robots to accurately perceive and manipulate objects in unstructured environments. By fusing deep neural networks with 3D point cloud data, Wei’s approach enhances real-time target detection and grasping precision—key for smart factory automation. Though his citation count is currently modest (4 citations), his research aligns with the explosive growth of human-machine collaborative industries, where demand is shifting from isolated applications to broad industrial categories. Wei’s contributions are particularly relevant as manufacturing evolves toward flexible, vision-guided robotics. His work signals a promising trajectory in applied AI for robotics, offering foundational methods that could scale across logistics, assembly, and quality inspection. For students and researchers, Wei represents a new wave of engineers bridging computer vision and mechanical control to make industrial robots safer, smarter, and more adaptable.
Research Focus
Key Achievements
Top Papers
- 1