Pengfei Lin
Papers
1
Total Citations
20
H-Index
1
About
Pengfei Lin is a researcher whose work sits at the intersection of autonomous navigation, path planning, and intelligent vehicle control. His primary research areas include collision avoidance systems, trajectory optimization, and waypoint tracking for mobile robots and autonomous vehicles. Lin’s most notable contribution is the development of a novel potential field-based model curve fitting method (PF-MCF), which integrates clothoid curves for emergency collision avoidance during waypoint tracking. This approach addresses a critical challenge in real-time obstacle avoidance by combining the computational efficiency of potential fields with the smoothness and feasibility of clothoid trajectories, offering a practical solution for dynamic environments. His work has garnered attention, with his top-cited paper accumulating 20 citations since 2022, reflecting its relevance to both academic research and applied autonomous systems. Lin’s contributions are particularly valuable for advancing the safety and reliability of autonomous navigation in complex scenarios, such as following a leading vehicle while avoiding unexpected obstacles. His research continues to influence the development of more responsive and intelligent path-planning algorithms.
Research Focus
Key Achievements
Top Papers
- 1