Yuqi Zhang

Nanjing University of Aeronautics and Astronautics

Papers

Total Citations

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About

Yuqi Zhang is a leading researcher in computer vision and robotic manipulation, with a focus on high-precision 6D pose estimation for automated assembly. His work addresses the critical challenge of enabling robots to accurately perceive and interact with objects in complex, real-world environments, particularly those that are texture-less or operating in large-scale spaces. Zhang’s major contributions include the development of novel deep learning architectures and 3D descriptors that achieve robust pose estimation under adverse conditions like variable lighting, occlusion, and clutter. His most cited paper, "EANet: Edge-Attention 6D Pose Estimation Network for Texture-Less Objects" (2022, 37 citations), introduces an edge-attention mechanism to overcome the difficulties posed by texture-less surfaces. This is complemented by his work on a high-accuracy pose measurement system for large-scale robotic assembly (2021, 34 citations) and the BOLD3D descriptor (2020, 11 citations), which collectively form a powerful toolkit for industrial automation. Zhang’s research directly impacts the reliability and precision of vision-based measurement systems, pushing the boundaries of what robots can achieve in manufacturing and assembly tasks.