Chengwan An
Papers
1
Total Citations
2
H-Index
1
About
Chengwan An’s research focuses on mobile robot navigation and computer vision, with a particular emphasis on landmark-based self-localization for indoor environments. Their most notable contribution is the development of an adaptive doorplate detection and recognition system, which enables mobile robots to identify and interpret doorplates as visual landmarks for precise self-localization. This work, published in 2005, addresses a critical challenge in robotics: how to navigate without relying on memory-intensive environmental maps. By using doorplates—common, information-rich features in indoor settings—An’s approach simplifies localization while enhancing accuracy. Although the paper has garnered 2 citations to date, its conceptual foundation has informed subsequent research in landmark-based navigation. An’s work stands out for its practical, low-complexity solution to a fundamental robotics problem, offering a scalable alternative to more computationally demanding techniques. This contribution remains relevant for students and researchers exploring efficient, real-world robot navigation systems, particularly in structured indoor spaces like offices or hospitals.
Research Focus
Key Achievements
Top Papers
- 1