Xuecheng Xu
Papers
19
Total Citations
417
H-Index
7
About
Xuecheng Xu is a leading researcher in robotics, specializing in LiDAR-based global localization, place recognition, and dense mapping for autonomous navigation. His major contributions include developing innovative algorithms that enable robots to robustly determine their position and orientation in large-scale environments, even under significant viewpoint changes and appearance variations. Xu introduced DiSCO (2021, 103 citations), a differentiable scan context method that achieved robust global localization, and RING++ (2023, 72 citations), a roto-translation invariant approach for localization on sparse scan maps. His survey on global LiDAR localization (2024, 108 citations) has become a key reference, synthesizing challenges and advances in the field. Beyond localization, Xu developed GEM (2020, 31 citations), an online globally consistent dense elevation mapping system for unstructured terrain, and pioneered GPU-accelerated traversability mapping (2019, 24 citations) for real-time navigation. His work on collaborative localization of aerial and ground robots (2020) and heterogeneous sensor matching (2020) further demonstrates his versatility. With over 400 total citations, Xu's research directly addresses critical challenges in autonomous navigation, making him a prominent figure in robotics and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1A Survey on Global LiDAR Localization: Challenges, Advances and Open Problems108 citations · 2024
- 2DiSCO: Differentiable Scan Context With Orientation103 citations · 2021
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- 5GPU accelerated real-time traversability mapping24 citations · 2019
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