Guo-Jhen Sun

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About

Guo-Jhen Sun is a robotics and computer vision researcher whose work sits at the intersection of industrial automation, 3D pose estimation, and robotic grasping. His research focuses on developing intelligent vision-based systems that enable robotic manipulators to perceive, interpret, and interact with objects in unstructured environments — a critical challenge in modern manufacturing and automation. Sun's most recognized contribution, "Random Bin Picking with Multi-view Image Acquisition and CAD-Based Pose Estimation" (2018, 17 citations), advances the field of bin-picking robotics by addressing the limitations of traditional CAD-model approaches through multi-view image acquisition strategies. His subsequent work, "Robotic Grasping Using Semantic Segmentation and Primitive Geometric Model Based 3D Pose Estimation" (2020, 14 citations), demonstrates his progression toward integrating deep learning techniques — particularly semantic segmentation — with geometric modeling to enable more robust and adaptable robotic grasping in real-world factory settings. Collectively, Sun's research contributes practical, scalable solutions to longstanding challenges in visual servo control and automated manipulation. With over 30 citations across his key works, his contributions are gaining meaningful traction in the robotics community, making his research particularly relevant for engineers and scholars advancing intelligent industrial systems.