Papers
14
Total Citations
5,842
H-Index
12
About
Tong Qin is a prominent robotics and computer vision researcher whose work has profoundly shaped the field of visual-inertial state estimation and autonomous navigation. He is best known as the lead developer of **VINS-Mono**, a robust monocular visual-inertial odometry system that has become one of the most widely adopted frameworks in robotics and augmented reality, amassing over 4,390 citations since its publication in 2018. This landmark contribution demonstrated how a single low-cost camera and IMU could achieve reliable six-degree-of-freedom metric pose estimation — a breakthrough for lightweight platforms such as micro aerial vehicles. Qin's broader research spans multi-sensor fusion, sensor calibration, SLAM (Simultaneous Localization and Mapping), and dynamic object tracking. His general optimization-based frameworks for local and global pose estimation with multiple sensors reflect a sustained effort to make state estimation robust across diverse hardware configurations. He has also made important contributions to temporal and rotational calibration of heterogeneous sensors, addressing a critical practical challenge in real-world deployments. With over 5,000 cumulative citations, his work has had significant influence on autonomous driving, drone navigation, and extended reality systems, establishing him as a key figure in modern mobile robotics research.
Research Focus
Key Achievements
Top Papers
- 1VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator4,390 citations · 2018
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- 3Autonomous aerial navigation using monocular visual‐inertial fusion240 citations · 2017
- 4Online Temporal Calibration for Monocular Visual-Inertial Systems222 citations · 2018
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- 6Robust initialization of monocular visual-inertial estimation on aerial robots151 citations · 2017
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- 10SLAM-based localization of 3D gaze using a mobile eye tracker43 citations · 2018