Zejian Deng
Papers
1
Total Citations
12
H-Index
1
About
Zejian Deng is a researcher advancing the field of intelligent robotic manufacturing, with a primary focus on 3D vision-guided welding and additive manufacturing. His work centers on developing automated systems for complex weld cladding processes, particularly for multi-bead arc welding applications. Deng’s most-cited paper, "Point Cloud 3D Weldment Reconstruction and Welding Feature Extraction for Robotic Multi-bead Arc Weld Cladding Path Planning" (2024), has garnered 12 citations, demonstrating early impact in this specialized area. In this work, he introduced a novel method for reconstructing 3D weldment geometries from point cloud data and extracting critical welding features, enabling precise robotic path planning for multi-layer cladding. This contribution addresses a key challenge in automated welding: achieving accurate, adaptive toolpaths for complex, freeform surfaces. Deng’s research integrates computer vision, robotics, and materials processing, offering practical solutions for industries requiring high-precision, repeatable weld deposition. His work is particularly notable for bridging the gap between raw sensor data and actionable robotic commands, a critical step toward fully autonomous manufacturing. As a rising researcher, Deng’s contributions are laying the groundwork for smarter, more flexible robotic welding systems.
Research Focus
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Top Papers
- 1