Papers
4
Total Citations
78
H-Index
4
About
Xiaodong Tao is a leading researcher in robotics and autonomous navigation, with a focus on solving critical challenges in perception and state estimation. His work spans active optical systems for micro-manipulation, LiDAR-based SLAM, and advanced sensor fusion for unmanned aerial vehicles (UAVs). Tao’s major contributions include developing an active optical system that integrates robotics to overcome occlusion and limited field-of-view in microassembly (34 citations), and pioneering an artificial landmark-assisted 2D LiDAR SLAM method for indoor environments with insufficient features (25 citations). He has also advanced robust navigation through a variational Bayesian-based adaptive error-state Kalman filter for LiDAR-inertial systems (10 citations), addressing time-varying noise in real-world conditions. Notably, his fast and robust semidirect monocular visual-inertial odometry algorithm enables real-time pose estimation for UAVs (9 citations), pushing the boundaries of autonomous flight. With a strong citation impact and a focus on practical, real-world applications, Tao’s work is instrumental in enhancing robot autonomy in complex, feature-poor environments.
Research Focus
Key Achievements
Top Papers
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- 4Fast and Robust Semidirect Monocular Visual-Inertial Odometry for UAV9 citations · 2023