Xinlong Wen
Papers
1
Total Citations
1
H-Index
1
About
Xinlong Wen is a leading researcher in indoor localization and autonomous mobile robot navigation, with a focus on overcoming the challenges of complex, multi-building, and cross-floor environments. His most-cited work, "Reliable Indoor Localization in Multibuilding Environments: Leveraging Environment-Invariant and Position-Related Features" (2025), introduces a novel approach that harnesses environment-invariant and position-related features from Received Signal Strength Indicator (RSSI) data. This breakthrough addresses the fundamental limitation of low sampling accuracy in RSSI-based systems, significantly enhancing localization reliability without requiring expensive hardware. By enabling cost-effective, precise navigation in 3D indoor spaces, Wen’s contributions have practical implications for robotics, smart buildings, and IoT applications. His work is gaining traction, with citations already reflecting its relevance to the field. Wen’s research stands out for its innovative fusion of signal processing and spatial reasoning, offering a scalable solution to one of indoor robotics’ most persistent problems.
Research Focus
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Top Papers
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