Chen Sheng-nan
Papers
1
Total Citations
10
H-Index
1
About
Chen Sheng-nan is a robotics researcher whose work centers on autonomous navigation and terrain perception for mobile robots. Her most cited paper, "An Integrated Terrain Identification Framework for Mobile Robots: System Development, Analysis, and Verification" (2020), tackles a critical challenge in autonomous control: reliably identifying terrain parameters. By fusing inertial and driving current signals, her framework overcomes the instability of single-source approaches, enabling robots to adapt more intelligently to their environments. This contribution has garnered 10 citations and lays foundational groundwork for safer, more efficient autonomous systems in unstructured settings. Chen’s research is particularly relevant for field robotics, where terrain variability often limits performance. Her integrated methodology demonstrates a practical path toward robust real-world deployment, making her work a valuable reference for students and engineers developing next-generation autonomous vehicles and exploratory robots.
Research Focus
Key Achievements
Top Papers
- 1