Fanlin Zeng
Papers
1
Total Citations
10
H-Index
1
About
Fanlin Zeng is a researcher specializing in mobile robotics and environmental sensing, with a primary focus on odor source localization and mapping in complex, dynamic environments. His key research areas include multi-robot olfaction, airflow-adaptive algorithms, and information fusion techniques. Zeng’s major contribution lies in pioneering experimental studies on multiple odor source mapping under time-varying airflow conditions, where he developed a novel algorithm based on Dempster-Shafer (D-S) theory. This work addresses the challenging problem of detecting and mapping chemical plumes in outdoor settings with strong, unpredictable wind patterns—a critical capability for applications in environmental monitoring, hazardous material detection, and search-and-rescue operations. His 2016 paper, "Experimental study on multiple odor sources mapping by a mobile robot in time-varying airflow environment," has garnered 10 citations, reflecting its foundational role in advancing practical robotic olfaction. By demonstrating robust performance in real-world conditions, Zeng’s research bridges the gap between theoretical sensor fusion and field-deployable systems, establishing him as a notable contributor to autonomous environmental sensing.
Research Focus
Key Achievements
Top Papers
- 1