Papers
4
Total Citations
24
H-Index
2
About
Ruilan Gao is a robotics researcher whose work centers on advancing 3D reconstruction, simultaneous localization and mapping (SLAM), and multisensor fusion for autonomous navigation. Her major contributions lie in developing novel frameworks that bridge the gap between geometric accuracy and computational efficiency in large-scale, outdoor environments. Her most cited work, "LI-GS: Gaussian Splatting With LiDAR Incorporated for Accurate Large-Scale Reconstruction" (2024, 17 citations), tackles the persistent challenge of geometric precision in unbounded scenes by integrating LiDAR data with 3D Gaussian Splatting, a breakthrough for robotics applications requiring reliable spatial understanding. Gao also introduced "LFVB-BioSLAM" (2023), a bionic SLAM system that combines a lightweight LiDAR front end with a bio-inspired visual back end, offering a power-efficient alternative to traditional probabilistic optimization frameworks. Her "ER-Mapping" system (2024) further enhances robustness by employing residual evaluation and selection for colorized point cloud generation, while her latest work, "RISED" (2025), optimizes image selection and point cloud densification to improve colorized mapping accuracy. Through these innovations, Gao is shaping the future of autonomous robot perception, making her research essential reading for students and engineers working on real-world navigation and mapping systems.
Research Focus
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Top Papers
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