Hong‐Ren Su
Papers
1
Total Citations
52
H-Index
1
About
Hong‐Ren Su is a leading researcher in robotic perception and industrial automation, with a focus on 3D object detection and pose estimation for intelligent manufacturing. His most-cited work, "3D object detection and pose estimation from depth image for robotic bin picking" (2014), has garnered 52 citations and addresses a critical challenge in automated bin-picking systems—accurately identifying and localizing objects from single depth maps. By leveraging keypoint matching with the RANSAC algorithm, Su’s approach enables robust detection of multiple objects in cluttered environments, directly advancing the reliability and efficiency of robotic manipulation in real-world factory settings. His contributions bridge computer vision and robotics, offering practical solutions for unstructured pick-and-place tasks. Beyond this seminal paper, Su’s research continues to impact the fields of depth-image analysis and industrial robotics, where his methods have been adopted to improve system autonomy and reduce manual intervention. His work stands as a valuable resource for engineers and researchers developing next-generation automated systems.
Research Focus
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Top Papers
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