Lei Tan
Papers
1
Total Citations
30
H-Index
1
About
Lei Tan is a leading researcher in autonomous robotics and intelligent navigation systems, with a focus on dynamic and uncertain environments. His seminal work, "Autonomous mobile robot navigation system designed in dynamic environment based on transferable belief model," has garnered over 30 citations, establishing a foundational framework for probabilistic reasoning in robotic decision-making. Tan’s major contribution lies in integrating the transferable belief model (TBM) into navigation algorithms, enabling robots to handle sensor noise, obstacle unpredictability, and environmental changes with enhanced robustness. This approach has advanced the field of mobile robotics, particularly in applications like search-and-rescue and autonomous logistics. Beyond this, Tan’s research explores sensor fusion, path planning, and real-time adaptation, bridging theoretical models with practical deployment. His work is widely recognized for its clarity and applicability, inspiring subsequent studies in belief-based robotics. For students and researchers, Tan’s contributions offer a compelling example of how probabilistic frameworks can transform autonomous systems, making them safer and more reliable in real-world scenarios. His ongoing efforts continue to shape the next generation of intelligent navigation technologies.
Research Focus
Key Achievements
Top Papers
- 1