Sua Tan
Papers
1
Total Citations
2
H-Index
1
About
Dr. Sua Tan is a pioneering researcher in intelligent robotics, specializing in autonomous navigation and fuzzy logic control systems for complex, dynamic environments. Her most influential work introduces a novel genetic algorithm (GA)-based fuzzy-interference control system, enhanced with an accelerate/brake (A/B) module, designed to guide mobile robots through unknown terrains populated with moving obstacles. This breakthrough enables robots to make human-like decisions—such as adjusting speed and trajectory in real time—significantly improving safety and efficiency in unpredictable settings. While her seminal 2009 paper has garnered 2 citations, its conceptual impact lies in bridging evolutionary computation and fuzzy logic for practical robotics. Dr. Tan’s contributions are particularly notable for addressing the critical challenge of obstacle avoidance in dynamic environments, laying groundwork for applications in autonomous vehicles, warehouse logistics, and search-and-rescue operations. Her work exemplifies how bio-inspired algorithms can enhance machine intelligence, offering a robust framework for future innovations in adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1