Papers
1
Total Citations
4
H-Index
1
About
Xulong Xu is a robotics researcher specializing in autonomous navigation and localization for mobile robots in complex indoor environments. His work focuses on integrating global and local path planning strategies to enable reliable robot movement in challenging, real-world settings such as airports. In his most cited paper, Xu introduces a method that combines Ultra Wideband (UWB) sensors for precise global positioning with the A* algorithm for optimal global pathfinding, while simultaneously leveraging local cost maps to adapt to dynamic obstacles. This dual-layer approach addresses a critical challenge in indoor robotics: maintaining both efficiency and safety in uncertain, crowded spaces. Though early in his career, with his key paper accumulating 4 citations, Xu’s contribution is notable for its practical application to airport logistics and service robotics, where robust navigation is essential. His work represents a meaningful step toward deploying autonomous wheeled robots in large-scale public facilities, bridging the gap between theoretical path planning and real-world deployment.
Research Focus
Key Achievements
Top Papers
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