Tongqian Liu
Papers
2
Total Citations
12
H-Index
2
About
Tongqian Liu is a researcher focused on advancing indoor mobile robot navigation through the fusion of vision and inertial navigation systems (INS). Their key contributions lie in developing robust positioning algorithms that overcome the limitations of individual sensors, particularly in challenging environments like sharp turns. Liu’s most cited work, "Indoor Vision/INS Integrated Mobile Robot Navigation Using Multimodel-Based Multifrequency Kalman Filter" (2021), introduces a novel multimodel approach to improve positioning accuracy by adaptively fusing visual and inertial data at different frequencies. This method addresses the critical issue of visual data degradation during robot rotations, enhancing reliability in real-world applications. With 10 citations, this paper demonstrates growing influence in the field. Another notable work, "Research on Positioning Algorithm of Indoor Mobile Robot Based on Vision/INS" (2020), further explores sensor fusion strategies. Liu’s research is pivotal for autonomous systems in GPS-denied environments, such as warehouses or hospitals, where precise navigation is essential. Their work on multifrequency filtering and multimodel integration represents a significant step toward more resilient and accurate indoor robotics.
Research Focus
Key Achievements
Top Papers
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- 2