Papers
10
Total Citations
192
H-Index
6
About
Ruyu Liu is a robotics and computer vision researcher whose work centers on simultaneous localization and mapping (SLAM), multi-robot collaboration, and intelligent environment perception. His most influential contribution, "Intelligent Collaborative Localization Among Air-Ground Robots for Industrial Environment Perception" (2018, 96 citations), demonstrated how coordinated aerial and ground robots can achieve precise localization in complex industrial settings — a landmark result that has shaped subsequent multi-robot systems research. Liu has consistently pushed the boundaries of visual SLAM, authoring comprehensive surveys on semantic vSLAM that bridge traditional geometric approaches with deep learning-based scene understanding, and developing systems such as 360ORB-SLAM for panoramic imaging. His cross-modal depth completion work addresses real-world challenges in hospital robotics and large-scale indoor mapping, reflecting a strong applied orientation. Liu also advances sensor fusion, contributing tightly coupled LiDAR-inertial SLAM and novel LiDAR-camera calibration methods. Notably, his research extends into medical robotics, including depth estimation for intestinal endoscopy, and human-robot interaction through sign language recognition. With over 190 cumulative citations, Liu's diverse yet cohesive body of work represents meaningful progress in enabling robots to perceive, navigate, and interact intelligently across demanding real-world environments.
Research Focus
Key Achievements
Top Papers
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- 3Semantic Visual Simultaneous Localization and Mapping: A Survey19 citations · 2025
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- 5Semantic Visual Simultaneous Localization and Mapping: A Survey9 citations · 2022
- 6Tightly Coupled 3D Lidar Inertial SLAM for Ground Robot6 citations · 2023
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