Xiaoming Dong
Papers
2
Total Citations
12
H-Index
2
About
Xiaoming Dong is a researcher specializing in indoor robotics, with a particular focus on localization and motion estimation in GPS-denied environments. His work addresses the critical challenge of enabling autonomous robot navigation indoors, where traditional satellite positioning is unavailable. Dong’s major contributions include developing a motion estimation method for indoor robots using image sequences combined with an improved particle filter, which enhances tracking accuracy in complex environments. He also proposed a novel approach to indoor robot localization that integrates feature clustering with wireless sensor networks, tackling the persistent issue of localization robustness. Although his citation counts are modest—with his top-cited papers receiving 7 and 5 citations respectively—his research represents foundational steps toward more reliable autonomous service robots. By combining computer vision techniques with sensor network data, Dong’s work offers practical solutions for real-world indoor navigation challenges, making it relevant for students and researchers interested in robotics, sensor fusion, and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2