Qin-Yuan Meng
Papers
1
Total Citations
2
H-Index
1
About
Qin-Yuan Meng is a researcher in mobile robotics and indoor mapping, with a focus on advancing laser-based perception systems. Their key contributions lie in developing algorithms to enhance the accuracy and completeness of 2D LiDAR data, particularly for indoor environments. In their notable 2023 work, "A Laser Data Compensation Algorithm Based on Indoor Depth Map Enhancement," Meng addresses a critical limitation of standard 2D LiDAR scanners—their inability to detect objects below a fixed scanning plane. By integrating depth map enhancement techniques, Meng’s algorithm compensates for missing data, improving obstacle detection and mapping fidelity. This work has garnered 2 citations, signaling early recognition in the robotics community. Meng’s research is pivotal for applications like autonomous navigation and indoor robotics, where reliable environmental sensing is essential. Their approach bridges the gap between cost-effective 2D LiDAR and the richer data typically provided by 3D sensors, offering a practical solution for real-world deployment. As the field of mobile robotics expands, Meng’s contributions to sensor data compensation and indoor mapping continue to inform safer and more efficient robotic systems.
Research Focus
Key Achievements
Top Papers
- 1