Tong Duan
Papers
1
Total Citations
2
H-Index
1
About
Tong Duan is a researcher whose work lies at the intersection of computational intelligence, robotics, and perception-based systems. Their key research areas include rough-fuzzy theory, autonomous navigation, and vision-based control for mobile robots. Duan’s major contribution is the development of a novel rough-fuzzy perception-based computing approach, which extends conventional fuzzy control methods to enhance robotic decision-making in uncertain environments. This work is exemplified in their most-cited paper, "A rough-fuzzy perception-based computing for a vision-based wall-following robot" (2014), which has garnered 2 citations. While the citation count is modest, the research represents a foundational step in integrating rough set theory with fuzzy logic for more robust, adaptive robot behavior. Duan’s approach is particularly notable for enabling indoor robots to follow walls in compact, complex spaces, demonstrating practical applications in autonomous navigation. This work contributes to the broader field of intelligent systems, offering a novel framework for perception-based computing that could inspire future advances in robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1