Xing Zheng
Papers
1
Total Citations
4
H-Index
1
About
Xing Zheng is a researcher advancing the frontiers of intelligent robotics and human-machine interaction, with a focus on integrating deep learning with 3D perception for industrial automation. Their most-cited work, "Research of robotic arm control system based on deep learning and 3D point cloud target detection algorithm" (2022), addresses a critical challenge in smart manufacturing: enabling robots to accurately perceive and manipulate objects in unstructured environments. By combining 3D point cloud processing with deep neural networks, Zheng’s system enhances robotic arm precision and adaptability, supporting the shift from rigid automation to flexible, intelligent production lines. Though early in their career, with 4 citations on this key paper, Zheng’s research aligns with the explosive growth of human-machine collaborative industries, impacting sectors from assembly to logistics. Their work contributes to the broader vision of Industry 4.0, where robots not only execute tasks but understand their surroundings in real time. Zheng’s contributions are particularly relevant for researchers exploring sensor fusion, real-time control, and the practical deployment of AI in robotics.
Research Focus
Key Achievements
Top Papers
- 1