Long Thanh Ngo
Papers
7
Total Citations
30
H-Index
3
About
Long Thanh Ngo is a leading researcher in the application of type-2 fuzzy logic systems to autonomous robotics, with a particular focus on robot navigation and obstacle detection. His work addresses the critical computational bottlenecks of type-2 fuzzy logic systems (T2FLSs), pioneering the use of GPU acceleration to dramatically speed up calculations for real-time navigation tasks. Ngo has made foundational contributions to extending fuzzy directional relationships for collision avoidance behavior and developing novel approaches for obstacle detection using depth and RGB-D camera streams. His innovative use of refinement constraint triangulated irregular networks (CTIN) for representing general type-2 fuzzy sets has helped reduce computational complexity in these systems. Among his most cited works are his 2012 paper on GPU-based speedup of interval type-2 fuzzy logic systems (9 citations) and his 2006 work on fuzzy directional relationships for mobile robot collision avoidance (6 citations). Ngo’s research bridges the gap between theoretical fuzzy logic advances and practical robotic applications, making autonomous navigation more efficient and reliable in complex, uncertain environments.
Research Focus
Key Achievements
Top Papers
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- 3Refinement CTIN for general type-2 fuzzy logic systems4 citations · 2011
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