Shoufeng Jin
Papers
4
Total Citations
27
H-Index
3
About
Shoufeng Jin is a leading researcher in intelligent robotics and industrial automation, with a primary focus on visual perception, path planning, and autonomous manipulation for manufacturing systems. His most impactful work introduces a Kinect V2-based method for 3D point cloud processing, enabling yarn-bobbin-handling robots to achieve visual recognition and grasping without human dependence—a contribution that has garnered 11 citations and addresses critical labor shortages in textile industries. Jin further advanced mobile robot autonomy through a whale optimization algorithm for intelligent path planning, cited 9 times, which leverages swarm intelligence to navigate complex environments. His multi-target visual recognition and positioning methods for sorting robots (5 citations) tackle challenges of random object placement, while his novel information fusion approach using an improved SURF algorithm enhances industrial robot localization speed and accuracy. Collectively, Jin’s work integrates computer vision, optimization algorithms, and robotic control to push the boundaries of smart manufacturing, offering practical solutions that reduce human intervention and improve efficiency in real-world production lines.
Research Focus
Key Achievements
Top Papers
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- 2Research on robot path planning based on whale optimization algorithm9 citations · 2021
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