Simin Zhan
Papers
2
Total Citations
7
H-Index
2
About
Simin Zhan is a rising researcher in intelligent robotics and 3D computer vision, with a focused interest in advancing industrial automation through sensor fusion and deep learning. Her work bridges the critical gap between perception and robotic manipulation, particularly in manufacturing environments. Zhan’s most cited paper, “Hand-eye Calibration of Industrial Robots with 3D Cameras based on Dual Quaternions” (2022, 4 citations), introduces a novel calibration method using 3D depth cameras and specially designed cube-shaped calibrators. This approach simplifies the traditionally complex process of establishing coordinate correspondences between a robot’s arm and its vision system, enabling more precise guidance for automated tasks. In her second highly cited work, “Weld Seam Segmentation in RGB-D Data using Attention-based Hierarchical Feature Fusion” (2022, 3 citations), Zhan tackles the challenging problem of weld detection for robotic milling. By fusing color and depth information with an attention mechanism, her method achieves accurate segmentation of multiple welds with varying morphologies on a single workpiece—a crucial step for autonomous post-weld processing. Though early in her career, Zhan’s contributions are already shaping how industrial robots perceive and interact with complex, real-world objects, laying the groundwork for more flexible and intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2