Naixin Fan

Carnegie Mellon University

Papers

1

Total Citations

40

H-Index

1

About

Naixin Fan is a roboticist whose research lies at the intersection of bio-inspired locomotion, control systems, and adaptive robotics. Her most cited work, “Central Pattern Generator With Inertial Feedback for Stable Locomotion and Climbing in Unstructured Terrain” (2018, 40 citations), introduces a novel framework that integrates vertebrate-inspired central pattern generators (CPGs) with inertial sensory feedback. This approach enables articulated robots—whether crawling, swimming, or legged—to dynamically adapt their gaits in real time, achieving stable locomotion and climbing on uneven, unpredictable surfaces. By bridging neural control principles with practical robotic design, Fan’s contributions offer a pathway toward more resilient, autonomous machines capable of navigating complex environments. Her work has been recognized for its potential to advance field robotics, search-and-rescue operations, and extraterrestrial exploration. With a growing citation impact, Fan continues to shape how robots perceive and respond to their surroundings, making her a rising voice in the field of bio-inspired robotics and adaptive control.

Research Focus

Key Achievements

1
H-Index
1
Papers
40
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
Central Pattern Generator With Inertial Feedback for Stable Locomotion and Climbing in Unstructured Terrain
40 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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