Yisen Hu
Papers
1
Total Citations
2
H-Index
1
About
Yisen Hu is a researcher advancing the reliability and precision of micro-electromechanical systems (MEMS) LiDAR technology, with a core focus on adaptive measurement, trajectory correction, and error evaluation. His most cited work, "Adaptive Dynamic Measurement, Trajectory Correction, and Error Evaluation Method in MEMS LiDAR System" (2025), tackles a critical challenge in autonomous sensing: external mechanical disturbances that cause trajectory deformations and incoherent 2D point cloud sampling. Hu proposed a novel real-time measurement framework that dynamically suppresses trajectory errors, enhancing the robustness of LiDAR systems in real-world environments. This contribution directly impacts the development of safer, more accurate perception systems for autonomous vehicles and robotics. With 2 citations already in its publication year, Hu’s work is gaining early recognition for addressing a practical bottleneck in MEMS LiDAR deployment. His research sits at the intersection of sensor physics, signal processing, and adaptive control, offering tangible solutions for high-precision 3D imaging. For students and researchers in optical engineering and autonomous systems, Hu’s work exemplifies how targeted error-correction methods can transform sensor performance under dynamic conditions.
Research Focus
Key Achievements
Top Papers
- 1