Zhuo Yan

Papers

1

Total Citations

17

H-Index

1

About

Zhuo Yan is a researcher in robotics and autonomous systems, with a primary focus on real-time path planning and obstacle avoidance. Their most notable contribution is an improved artificial potential field method that addresses two critical limitations of traditional approaches: local minima traps and oscillatory behavior in narrow passages. This work, published in 2018, has garnered 17 citations and provides a more reliable solution for robot navigation in complex environments. Yan's research is particularly relevant to applications requiring dynamic, real-time decision-making, such as mobile robotics and autonomous vehicles. By enhancing the efficiency and stability of path planning algorithms, their work helps bridge the gap between theoretical control methods and practical deployment. Yan's contributions are valuable for students and researchers seeking to understand and advance the state of the art in robotic motion planning.

Research Focus

Key Achievements

1
H-Index
1
Papers
17
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Real Time Robot Path Planning Method Based on Improved Artificial Potential Field Method
17 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago