Nai‐Wen Chang
Papers
2
Total Citations
72
H-Index
2
About
Nai-Wen Chang is a leading researcher in robotics and intelligent control systems, with a focus on autonomous navigation, human-robot interaction, and sensor fusion. Their pioneering work on fuzzy decentralized sliding-mode control (FDSMC) for car-like mobile robots, published in 2008, introduced a novel approach to trajectory tracking and dynamic obstacle avoidance within distributed sensor-network spaces—a contribution that has earned 43 citations and laid the groundwork for robust multi-robot coordination. Chang further advanced assistive robotics with a 2009 study on human tracking and following, integrating a single vision sensor and laser range finder for compact, cost-effective mobile companion robots. This sensor fusion method, cited 29 times, demonstrated that reliable person-following could be achieved without stereo-vision, enhancing the practicality of service robots in real-world environments. By combining theoretical control innovation with applied sensor integration, Chang’s work has significantly influenced the development of safer, more responsive autonomous systems, making their research essential reading for students and engineers in robotics, control theory, and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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