Yadong Zhang

China Railway Group (China)

Papers

1

Total Citations

36

H-Index

1

About

Yadong Zhang is a researcher whose work lies at the intersection of robotics, artificial intelligence, and dynamic systems control. His primary research focuses on developing intelligent path-planning algorithms for mobile robots operating in unpredictable environments. Zhang’s most notable contribution is the integration of fuzzy artificial potential fields with extensible neural networks, a novel approach that enables robots to navigate safely and efficiently amid moving obstacles. This work, published in 2020 and cited 36 times, has been recognized for its practical applicability in autonomous navigation, particularly in scenarios requiring real-time adaptation. By blending fuzzy logic’s handling of uncertainty with neural network adaptability, Zhang has advanced the field of mobile robotics, offering a robust solution to the longstanding challenge of collision-free path planning in dynamic settings. His research continues to influence both academic studies and industrial applications, where reliable autonomous movement is critical. Zhang’s work stands out for its elegant synthesis of classical and modern AI techniques, making him a notable figure in the ongoing evolution of intelligent robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
36
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
Path planning of mobile robot in dynamic environment: fuzzy artificial potential field and extensible neural network
36 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: China Railway Group (China)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago