Yang Shang

National University of Defense Technology

Papers

Total Citations

H-Index

About

Yang Shang is a researcher advancing the field of robotic perception and computer vision, with a focus on pose estimation for industrial automation. His key research areas include 6D object pose estimation, camera geometry, and robotic assembly. Shang’s major contribution lies in developing reconstruction-based methods for robust pose estimation, addressing challenges such as diverse object shapes and complex environments in industrial settings. His 2020 paper on “Reconstruction-based 6D pose estimation for robotic assembly,” with 4 citations, provides a practical solution for applications like bin picking and collaborative robotics, enhancing accuracy and reliability. Additionally, his 2023 work on solving the generalized pose problem for central and non-central cameras, though newly published with 1 citation, demonstrates his commitment to expanding theoretical frameworks in camera geometry. Shang’s research bridges the gap between algorithmic innovation and real-world robotic tasks, making his work valuable for students and engineers in automation and computer vision. His achievements highlight a promising trajectory in enabling more precise and adaptable robotic systems for manufacturing and assembly lines.