Papers
2
Total Citations
10
H-Index
2
About
Manhui Sun is a researcher specializing in robotics perception, with a core focus on visual localization and navigation in GPS-denied environments. Her work addresses the critical challenge of enabling mobile robots to determine their position accurately when satellite signals are unavailable, such as in disaster sites or indoor areas. Sun’s major contributions lie in developing novel methods for monocular camera localization within large-scale 3D LiDAR maps. Her most cited paper, "Scale‐aware camera localization in 3D LiDAR maps with a monocular visual odometry" (2019, 6 citations), introduces a framework that bridges visual and LiDAR data for robust, scale-aware positioning. She further advanced the field with her work on "Convolutional neural network-based coarse initial position estimation of a monocular camera in large-scale 3D light detection and ranging maps" (2019, 4 citations), which leverages deep learning to solve the critical "kidnapped robot problem"—estimating a robot’s starting location from scratch. By integrating visual odometry with LiDAR maps and applying convolutional neural networks for global localization, Sun has provided practical, scalable solutions for autonomous navigation in complex, unstructured environments. Her research is foundational for students and engineers working on robust perception systems for field robotics.
Research Focus
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Top Papers
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