Xin Nie
Papers
1
Total Citations
6
H-Index
1
About
Xin Nie is a researcher whose work focuses on multi-sensor calibration for autonomous driving and robotics, particularly in simultaneous localization and mapping (SLAM). His major contribution is the development of a two-step self-calibration method for LiDAR-GPS/IMU systems, which addresses the critical challenge of accurately estimating extrinsic parameters between sensors. This work, published in 2023, has already garnered 6 citations, highlighting its relevance and impact in the field of multi-sensor fusion. By improving calibration accuracy, Nie’s research directly enhances the performance of autonomous systems, enabling more reliable navigation and mapping. His approach, based on the hand-eye method, offers a practical and efficient solution for real-world applications. Nie’s contributions are essential for advancing the robustness of sensor integration in autonomous vehicles and robotics, making his work a valuable resource for students and researchers exploring sensor fusion and SLAM technologies.
Research Focus
Key Achievements
Top Papers
- 1Two-Step Self-Calibration of LiDAR-GPS/IMU Based on Hand-Eye Method6 citations · 2023