Shengjie Huang
Papers
2
Total Citations
11
H-Index
2
About
Shengjie Huang is a rising researcher in autonomous systems, specializing in multi-sensor calibration and LiDAR-based localization. His work addresses critical challenges in sensor fusion for autonomous vehicles and mobile robots, focusing on the precise alignment and integration of cameras, GNSS/IMU, and LiDAR systems. Huang’s major contributions include developing a target-free self-calibration method for stereo camera-GNSS/IMU systems, which eliminates the need for specific vehicle movements or calibration targets, significantly simplifying real-world deployment. This work has garnered 6 citations since 2023. He also advanced LiDAR odometry and mapping with the WiCRF2 framework, which introduces multi-weighted feature extraction and motion observability constraints to enhance SLAM accuracy and robustness in challenging environments, earning 5 citations. By tackling the practical hurdles of sensor fusion—from calibration to real-time localization—Huang’s research directly supports the reliability of low-cost, lightweight perception systems. His iterative refinement and observability-based approaches are paving the way for more resilient autonomous navigation, making his work essential reading for engineers and researchers building next-generation robotic platforms.
Research Focus
Key Achievements
Top Papers
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- 2