Tiantian Feng
Papers
3
Total Citations
16
H-Index
2
About
Tiantian Feng is a leading researcher in the field of robotics, with a primary focus on 3D mapping and simultaneous localization and mapping (SLAM) for autonomous systems. His work addresses critical challenges in large-scale environment perception, particularly in developing accurate and reliable neural implicit representations. Feng’s major contributions include the introduction of N³-Mapping, a pioneering method that leverages normal-guided neural non-projective signed distance fields for dense mapping, achieving high-quality 3D reconstruction in expansive spaces. This work, published in 2024, has already garnered 8 citations, reflecting its immediate impact. He further advanced the field with UN³-Mapping, which integrates uncertainty estimation into neural mapping, enhancing map reliability for safety-critical robot applications. In multi-robot SLAM, Feng developed a robust loop closure selection method based on inter- and intra-robot consistency, addressing the persistent problem of false positives from perceptual aliasing to ensure consistent global map fusion. With a growing citation record and a focus on practical, scalable solutions, Feng’s research is shaping the next generation of autonomous navigation and mapping technologies.
Research Focus
Key Achievements
Top Papers
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