Chun-Lin Lee
Papers
1
Total Citations
2
H-Index
1
About
Chun-Lin Lee is a robotics researcher whose work centers on intelligent human-robot interaction, autonomous navigation, and assistive mobile systems. His most-cited paper, “Equipped with Monocular Depth Estimation and Intelligent Wake-Up Vision Based Tracking System for a Human-Following Mobile Robot” (2024, 2 citations), addresses a critical challenge in service robotics: enabling robots to autonomously detect, wake up to, and follow a human user in real-world environments. By integrating monocular depth estimation with a vision-based wake-up mechanism, Lee’s system reduces computational load while maintaining robust tracking—a practical step toward affordable, responsive service robots for homes, healthcare, and social settings. His work reflects a broader interest in deploying intelligent robots as “good assistants” for daily life, from family care to medical support. Though early in his citation impact, Lee’s contributions are notable for bridging computer vision and embedded systems to create context-aware, human-centered robots. His research aligns with the growing demand for socially assistive robots that operate safely and intuitively alongside people, making him a promising voice in the field of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1