Xinrui Meng
Papers
1
Total Citations
10
H-Index
1
About
Xinrui Meng is a leading researcher in robotics perception, with a primary focus on simultaneous localization and mapping (SLAM) and 3D reconstruction for indoor ground wheeled robots. Her most impactful contribution is the development of CID-SIMS—the Complex Indoor Dataset with Semantic Information and Multi-Sensor Data—published in 2023. This dataset has already garnered 10 citations, serving as a critical benchmark for advancing SLAM and 3D reconstruction in challenging indoor environments. By integrating semantic information with multi-sensor data, Meng’s work directly addresses real-world applications such as floor-sweeping robots and autonomous food delivery systems, where robust navigation and environmental understanding are essential. Her research bridges the gap between theoretical SLAM algorithms and practical deployment, enabling robots to operate reliably in cluttered, dynamic indoor spaces. CID-SIMS provides researchers with a standardized platform to test and improve semantic SLAM techniques, making it a foundational resource in the field. Meng’s contributions are particularly notable for their emphasis on leveraging semantic cues—like object recognition and scene understanding—to enhance localization accuracy and map fidelity, paving the way for more intelligent and autonomous service robots.
Research Focus
Key Achievements
Top Papers
- 1