Yuyuan Du

Papers

Total Citations

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About

Yuyuan Du is a researcher at the forefront of intelligent robotics and computer vision, with a focused interest in integrating deep learning algorithms into industrial automation systems. Their most cited work, "Research on Robotic Arm Based on YOLO" (2022), demonstrates a practical application of object detection technology—specifically, the YOLO algorithm—to enable visual guidance for robotic manipulators. By creating custom datasets tailored to industrial environments, Du trained the system to accurately identify and capture specified targets, bridging the gap between theoretical computer vision and real-world robotic control. This contribution highlights their ability to solve tangible engineering challenges, enhancing the autonomy and precision of industrial robots. Though early in their citation trajectory, Du’s work signals a promising impact on the field of robotics and automation, offering a scalable approach to integrating AI-driven perception into manufacturing and logistics. Their research is particularly valuable for students and engineers seeking to understand how state-of-the-art object detection can be seamlessly embedded into robotic systems for practical, industry-ready solutions.