Shouxin Yan

Beihang University

Papers

2

Total Citations

13

H-Index

2

About

Shouxin Yan is a leading researcher in intelligent robotic manufacturing, with a focus on the automation of complex industrial processes. His work centers on developing model-free path planning methods for robotic grinding, particularly for large, intricate forged parts—a critical challenge in heavy machinery and aerospace manufacturing. Yan’s most-cited paper, "Point cloud-based model-free path planning method of robotic grinding for large complex forged parts" (2024, 10 citations), introduces a groundbreaking approach that leverages 3D point cloud data to generate adaptive grinding paths without requiring pre-existing CAD models, significantly enhancing flexibility and precision in real-world applications. His earlier work, "An Intelligent Path Generation Method of Robotic Grinding for Large Forging Parts" (2021, 3 citations), laid the foundation for this innovation, demonstrating the potential of intelligent algorithms to optimize tool trajectories. Yan’s contributions are pivotal for advancing autonomous robotic systems in manufacturing, reducing human intervention, and improving efficiency. His research not only addresses practical industrial needs but also inspires further exploration into sensor-driven, model-free robotics, marking him as a rising figure in the field of intelligent automation.

Research Focus

Key Achievements

2
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Point cloud-based model-free path planning method of robotic grinding for large complex forged parts
10 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Beihang University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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