Haosong Yue
Papers
14
Total Citations
144
H-Index
7
About
Haosong Yue is a robotics researcher whose work bridges perception, navigation, and control for autonomous systems operating in complex environments. His key research areas include simultaneous localization and mapping (SLAM), loop closure detection, multi-sensor fusion, and legged robot locomotion. Yue’s most impactful contribution is a robust loop closure detection algorithm based on Bag of SuperPoints and graph verification (2019, 39 citations), which corrects accumulated localization errors during long-duration robot missions. He has also advanced 3D modeling with single Kinect sensors (36 citations) and real-time obstacle detection for legged robots (11 citations), enabling platforms like quadruped robots to traverse steps and grooves that challenge wheeled vehicles. Yue’s work extends to UAV visual SLAM, depth fusion using LiDAR, ToF, and binocular cameras, and gait generation with smooth speed transitions. Notably, he has contributed to robotics education through a Webots-based simulation framework for senior undergraduates and provided critical corrections to prior SLAM literature. With over 135 total citations across these ten papers, Yue’s research has practical impact on autonomous navigation, sensor integration, and educational tools for robot engineering.
Research Focus
Key Achievements
Top Papers
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- 2Fast 3D modeling in complex environments using a single Kinect sensor36 citations · 2013
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- 8LiDAR-ToF-Binocular depth fusion using gradient priors6 citations · 2020
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