Papers
3
Total Citations
48
H-Index
3
About
Dai Yating is a researcher specializing in mobile robot localization and navigation, particularly in GPS-denied indoor environments. Her work focuses on fusing multiple sensor modalities—including inertial measurement units (IMU), stereo vision, and ultrasound—to overcome the limitations of individual positioning systems. Her most cited paper (30 citations) introduces a dual Kalman filter approach that integrates IMU and stereo vision for real-time, accurate indoor localization, addressing the drift errors inherent in inertial systems. A second influential study (13 citations) proposes an asynchronous fusion method for binocular vision and inertial navigation, enhanced by fuzzy mapping, to improve robustness in complex indoor settings. Her research also explores low-cost INS-ultrasound fusion (5 citations) to mitigate magnetic interference and cumulative errors. Collectively, Dai Yating’s contributions advance practical solutions for autonomous mobile robot navigation, offering efficient, sensor-fusion-based methods that balance accuracy, cost, and real-time performance—critical for applications in logistics, service robotics, and industrial automation.
Research Focus
Key Achievements
Top Papers
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