Jingren Wen
Papers
1
Total Citations
11
H-Index
1
About
Jingren Wen is a researcher specializing in autonomous vehicle localization, LiDAR-based mapping, and robust navigation in GNSS-denied environments. Their major contribution lies in developing real-time, high-precision localization systems that overcome the drift and fragility of traditional SLAM methods. Wen’s most cited work, “Real-Time Scan-to-Map Matching Localization System Based on Lightweight Pre-Built Occupancy High-Definition Map” (2023, 11 citations), introduces a novel approach that leverages a pre-built, lightweight occupancy HD map to achieve drift-free, centimeter-level localization. This system is particularly impactful for autonomous vehicles and robots operating in urban canyons, tunnels, or other areas without reliable GPS. By replacing online SLAM with efficient scan-to-map matching, Wen’s work significantly improves robustness and computational efficiency, enabling practical deployment in real-world autonomous systems. Their research bridges the gap between high-definition mapping and real-time localization, offering a scalable solution for safe and reliable navigation. Wen’s contributions are foundational for advancing autonomous driving technology in challenging environments.
Research Focus
Key Achievements
Top Papers
- 1