Linhui Xiao

Papers

Total Citations

348

H-Index

About

Linhui Xiao is a leading researcher in robotics perception and multi-sensor fusion, with a primary focus on visual-inertial odometry (VIO), semantic SLAM, and sensor calibration for autonomous systems. Xiao’s most impactful contribution is the development of **Dynamic-SLAM**, a seminal work published in 2019 that has garnered over 344 citations. This paper pioneered a deep learning-based approach to monocular visual localization and mapping in dynamic environments, effectively addressing a critical limitation of traditional SLAM systems that assume a static world. By integrating semantic information, Dynamic-SLAM enables robots to robustly operate in real-world, crowded spaces. More recently, Xiao introduced **FDO-Calibr**, a novel frequency-domain optimization method for visual-aided IMU calibration, pushing the boundaries of sensor fusion accuracy. This work underscores Xiao’s commitment to solving foundational challenges in autonomous navigation. With a research portfolio that bridges theoretical innovation and practical deployment, Linhui Xiao continues to shape the future of robust, perception-driven robotics, making their work essential reading for students and engineers advancing autonomous systems.