Youjie Zhou

Shandong University, Beijing Information Science & Technology University, University of Jinan

Papers

Total Citations

H-Index

About

Youjie Zhou is a robotics researcher whose work focuses on advancing visual simultaneous localization and mapping (SLAM) and autonomous navigation, particularly in challenging environments. His key research areas include visual odometry, multimodal sensor fusion, and deep learning for robotic perception. Zhou’s most notable contribution is the development of a human visual attention mechanism-inspired point-and-line stereo visual odometry system, designed to maintain robust pose estimation even in scenes with unevenly distributed features—a common failure point for conventional algorithms. This work, published in 2023, has already garnered 5 citations. He has also pioneered multimodal fusion SLAM using Fourier attention mechanisms to improve performance under noise, poor lighting, and darkness, addressing critical limitations in real-world deployment. Additionally, Zhou has explored SLAM implementation on the Robot Operating System (ROS) and contributed a comprehensive review of deep learning-based image guidance technologies for surgical robots, highlighting pathways toward greater autonomy in medical robotics. His research, with papers accumulating citations from 2021 to 2025, demonstrates a clear trajectory toward making robots more perceptive and reliable in complex, real-world scenarios.