Linqigao Wu

Wuhan University of Science and Technology

Papers

Total Citations

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About

Linqigao Wu is a researcher advancing the intersection of robotics and machine vision, with a primary focus on intelligent automation for industrial applications. Wu’s key research areas include 6D pose estimation, robotic bin-picking, and machine vision-based sorting systems. Their most notable contribution is the development of the Curvature-based Point-Pair Features (Cur-PPF) method for 6D pose estimation, which addresses critical challenges in robotic bin-picking such as noise, occlusion, and object overlap. This work, published in 2022, has garnered 16 citations and represents a significant step toward improving robot grasping accuracy in cluttered environments. Wu also authored a comprehensive overview of intelligent sorting systems using machine vision (2023, 4 citations), demonstrating how traditional robots integrated with vision technology can reduce costs while boosting efficiency and precision. By tackling fundamental perception problems in robotics, Wu’s research directly supports the advancement of autonomous manufacturing and logistics. Their work is particularly valuable for students and engineers seeking practical solutions to real-world robotic manipulation challenges, bridging the gap between theoretical computer vision and deployable industrial systems.