Yongsen Chen
Papers
1
Total Citations
6
H-Index
1
About
Yongsen Chen is a researcher specializing in visual-inertial odometry (VIO), computer vision, and autonomous navigation, with a particular focus on robust state estimation in dynamic environments. His most notable contribution is the development of a real-time motion state estimation method for feature points based on optical flow fields, designed to enhance monocular VIO performance in challenging, dynamic scenes. This work, published in 2025, has already garnered 6 citations, reflecting its timely relevance to the field. Chen’s approach addresses a critical limitation of traditional VIO systems—their vulnerability to moving objects—by enabling accurate differentiation between static and dynamic features, thereby improving localization reliability. His research bridges the gap between theoretical computer vision and practical robotics applications, offering solutions that are both computationally efficient and robust. Chen’s work is particularly impactful for autonomous systems operating in real-world settings, such as self-driving cars and drones, where dynamic obstacles are common. With a focus on advancing real-time perception and navigation, Yongsen Chen continues to contribute to the next generation of intelligent, environment-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1