Leijiao Ge
Papers
3
Total Citations
38
H-Index
3
About
Leijiao Ge is a leading researcher in mobile robotics and intelligent sensing, with a focus on enabling reliable autonomous navigation in complex, real-world environments. His core contributions lie in robust localization for mobile robots, particularly under challenging conditions such as non-line-of-sight (NLOS) scenarios and distributed sensor networks. Ge’s 2019 work on enhancing localization in distributed environments (22 citations) established foundational methods for coordinating mobile robots with sensor nodes in physical proximity. He further advanced the field with a 2020 study on robust localization in industrial settings (11 citations), introducing novel measurement processing strategies and an improved particle filter to accurately identify and mitigate NLOS errors. More recently, Ge has tackled the practical challenge of industrial meter detection using few-shot learning and sim-to-real domain adaptation (2023, 5 citations), addressing the critical lack of large-scale annotated datasets for deep learning-based inspection robots. His work bridges the gap between theoretical localization algorithms and deployable solutions for industrial automation, making him a key figure in the advancement of autonomous robotic systems for manufacturing and infrastructure monitoring.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3