Hanzhang Xue

National University of Defense Technology

Papers

Total Citations

H-Index

About

Hanzhang Xue is a rising researcher in autonomous navigation and robotics, whose work focuses on advancing LiDAR-based place recognition (LPR) for self-driving vehicles and mobile robots. His core contributions address a critical challenge in simultaneous localization and mapping (SLAM): enabling reliable loop closure detection in large-scale, outdoor environments. In his 2025 paper "R2SCAT-LPR," Xue introduced a rotation-robust network that leverages self- and cross-attention transformers, achieving 5 citations and setting a new standard for handling orientation variations in LPR. His earlier work, "SG-LPR" (2024, 4 citations), pioneered the use of semantic guidance—treating high-level scene semantics as a discriminative feature to distinguish geometrically similar places, thereby boosting robustness to environmental changes. Together, these papers have garnered early recognition for their innovative fusion of transformer architectures and semantic reasoning, directly addressing the limitations of traditional 2D-based methods. Xue’s research is particularly notable for its practical impact on autonomous vehicle navigation and mobile robot re-localization, offering scalable solutions that enhance the reliability of SLAM systems in real-world, dynamic environments.