Yan-Jhang Shih
Papers
2
Total Citations
4
H-Index
2
About
Yan-Jhang Shih is a robotics researcher focused on advancing Simultaneous Localization and Mapping (SLAM) technology, a critical challenge for autonomous navigation. His work addresses fundamental bottlenecks in SLAM systems, particularly the degradation of localization accuracy as environmental landmarks increase. In his 2015 study on feature extraction for SLAM, Shih proposed a filtering method to discard erroneous measurements before applying triangulation, directly improving robot pose estimation in cluttered environments. His 2014 research tackled the persistent problem of incorrect data association by introducing a fuzzy filter combined with curvature-based matching, which reduces mismatches between current sensor readings and stored landmarks. While each of these foundational papers has garnered 2 citations, they represent early efforts to enhance SLAM robustness through intelligent preprocessing—a theme that continues to influence modern autonomous systems. Shih’s contributions are particularly relevant for researchers developing reliable navigation in complex, real-world settings where sensor noise and landmark density pose significant challenges. His work underscores the importance of data association quality in achieving stable, long-term SLAM performance.
Research Focus
Key Achievements
Top Papers
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- 2