Xiaoqiong Shi
Papers
2
Total Citations
21
H-Index
2
About
Xiaoqiong Shi is a leading researcher in robotics and autonomous navigation, specializing in visual-inertial SLAM (Simultaneous Localization and Mapping) for dynamic environments. Her major contribution is the development of D-VINS (Dynamic Adaptive Visual-Inertial SLAM), a groundbreaking framework that overcomes the critical limitation of traditional SLAM systems—their reliance on static environment assumptions. By integrating IMU priors and semantic constraints, D-VINS enables robots to robustly perceive and navigate in real-world scenes cluttered with moving objects, significantly enhancing localization accuracy and map stability. This work has garnered over 21 citations since its 2023 publication, reflecting its rapid impact on the field. Shi’s research addresses a fundamental challenge in autonomous exploration, bridging the gap between laboratory assumptions and practical deployment. Her innovative approach not only advances the theoretical foundations of SLAM but also provides a scalable solution for applications in service robotics, autonomous driving, and drone navigation. For students and researchers, Shi’s work exemplifies how combining sensor fusion with semantic understanding can push the boundaries of robotic perception in unstructured, dynamic environments.
Research Focus
Key Achievements
Top Papers
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