Baoguo Yu

Beijing Satellite Navigation Center, China Electronics Technology Group Corporation

Papers

Total Citations

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About

Baoguo Yu is a leading researcher in spatial artificial intelligence, with a focus on indoor and urban positioning technologies that bridge the gap between perception and real-world navigation. His work primarily spans vision-based localization, LiDAR-based simultaneous localization and mapping (SLAM), and sensor fusion for autonomous systems. Yu’s most cited paper, “Image‐Based Indoor Localization Using Smartphone Camera” (2021, 19 citations), addresses the critical challenge of accurate positioning in GPS-denied environments like airports and shopping malls, leveraging ubiquitous smartphone cameras to overcome multipath interference common in wireless methods. In his 2023 study on GNSS-Assisted LiDAR Odometry and Mapping (9 citations), he advanced the widely-used LOAM algorithm by integrating global navigation satellite system data, significantly improving robustness in complex urban settings—a key contribution for autonomous driving and service robotics. His recent work on vision-based instance segmentation and object localization (2023) further demonstrates his commitment to enabling precise spatial understanding for augmented reality and robotic platforms. With a growing citation record and a clear trajectory toward solving real-world positioning challenges, Baoguo Yu is establishing himself as a vital contributor to the next generation of intelligent navigation systems.