Papers
8
Total Citations
143
H-Index
6
About
Zerong Su is a leading researcher in mobile robotics, specializing in multi-robot coordination, autonomous navigation, and sensor fusion. His most impactful work addresses the critical challenge of simultaneous obstacle avoidance and target tracking for multiple wheeled mobile robots (MWMRs), where he pioneered distance- and velocity-based control methods that guarantee certified safety in shared workspaces—a contribution cited over 70 times across his key papers. Su has also made significant advances in global localization, developing novel sensor-fusion mechanisms that combine LiDAR with visual features to enable robust pose estimation even in geometrically simple or degraded environments. His research on degeneracy detection for LiDAR SLAM, using point-to-distribution geometric models, has improved system reliability in feature-poor settings like tunnels and corridors. More recently, Su has extended his work to unstructured outdoor environments, creating joint semantic-geometric mapping frameworks for autonomous mobile robotic sprayers used in mosquito control and disinfection. With over 140 total citations and a growing portfolio of high-impact publications from 2017 to 2025, Su’s work bridges fundamental theory and practical deployment, making him a key figure in the evolution of safe, long-term autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Global localization of a mobile robot using lidar and visual features35 citations · 2017
- 3
- 4A Study of Sensor-Fusion Mechanism for Mobile Robot Global Localization17 citations · 2019
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- 7
- 8Appearance-invariant Visual Localization for Long-term Navigation1 citations · 2024