Feiran Huang
Papers
1
Total Citations
24
H-Index
1
About
Feiran Huang is a researcher whose work lies at the intersection of autonomous navigation, robotics, and intelligent sensing systems. Their most notable contribution is the development of the Heuristic Monte Carlo Algorithm (HMCA), a novel approach that integrates Monte Carlo localization with the Discrete Hough Transform to enable real-time localization and mapping for unmanned ground vehicles (UGVs) in cluttered, noisy indoor environments. This work, published in 2020 and garnering 24 citations, addresses a critical challenge in autonomous navigation by improving both accuracy and computational efficiency. Huang’s research is particularly impactful for advancing the reliability of UGVs in real-world settings, such as warehouses or disaster zones, where sensor noise and environmental clutter often hinder performance. Beyond this flagship paper, their broader portfolio explores sensor fusion and adaptive algorithms for mobile robotics. With a growing citation footprint, Huang is establishing themselves as a contributor to practical, scalable solutions in autonomous systems—work that holds promise for both academic robotics research and industrial applications in logistics and exploration.
Research Focus
Key Achievements
Top Papers
- 1