Chenyu Ruan
Papers
1
Total Citations
67
H-Index
1
About
Chenyu Ruan is a rising researcher in robotics and computer vision, whose work centers on advancing simultaneous localization and mapping (SLAM) systems for dynamic, real-world environments. His most-cited paper, "DN-SLAM: A Visual SLAM With ORB Features and NeRF Mapping in Dynamic Environments" (2023), has already garnered 67 citations, reflecting its timely impact on the field. In this work, Ruan tackles two persistent challenges: maintaining accurate localization and building dense, consistent maps in scenes with moving objects. By integrating ORB feature-based tracking with Neural Radiance Fields (NeRF) for mapping, he proposes a hybrid framework that significantly improves robustness over traditional SLAM approaches. This contribution is particularly valuable for autonomous robots and augmented reality applications operating in unpredictable settings. Ruan’s research bridges classical geometric methods with modern neural representations, offering a practical path toward more resilient perception systems. His achievements underscore a commitment to solving foundational problems in spatial AI, making his work essential reading for students and researchers interested in the next generation of visual SLAM technology.
Research Focus
Key Achievements
Top Papers
- 1