Feiran Chen

National University of Defense Technology

Papers

3

Total Citations

88

H-Index

3

About

Feiran Chen is a leading researcher in autonomous robotic search and environmental sensing, with a focus on developing intelligent strategies for locating hazardous emission sources in complex, large-scale environments. Her work bridges cognitive science and robotics, introducing innovative algorithms that enable mobile sensors to navigate real-world constraints like road networks, obstacles, and forbidden areas. Chen’s most impactful contribution is the "Entrotaxis-Jump" hybrid search algorithm (2020, 39 citations), which optimizes the balance between exploration and exploitation for efficient source seeking in road-constrained areas. She further advanced the field with cognitive strategies for searching diffusive sources in obstructed environments (2020, 34 citations), demonstrating how robots can adapt to unknown layouts with restricted zones. Her recent work on multi-robot collaborative searching in chemical clusters (2021, 15 citations) addresses critical emergency response scenarios, proposing coordinated teams to rapidly pinpoint gas leak sources. Collectively, Chen’s research has garnered over 88 citations, establishing her as a key innovator in autonomous search theory and its application to industrial safety. Her algorithms offer practical solutions for disaster management, reducing response times in hazardous chemical incidents.

Research Focus

Key Achievements

3
H-Index
3
Papers
88
Total Citations
29
Avg Citations/Paper
🏆 Most Cited Paper
Entrotaxis-Jump as a hybrid search algorithm for seeking an unknown emission source in a large-scale area with road network constraint
39 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: National University of Defense Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago