Hui‐Wen Lin
Papers
1
Total Citations
12
H-Index
1
About
Hui-Wen Lin is a researcher specializing in robust localization and perception for autonomous mobile robots, with a particular focus on visual-inertial odometry (VIO) and semantic fusion in challenging indoor environments. Her most notable contribution is the development of YO-VIO, a multi-sensor semantic fusion localization system designed to overcome the limitations of traditional visual SLAM in dynamic indoor settings. While conventional VO and VIO systems struggle with moving objects and changing scenes, YO-VIO integrates semantic information to enable more reliable pose estimation for service robots. This work, published in 2021, has already garnered 12 citations, reflecting its timely relevance to the robotics community. Lin’s research addresses a critical gap in real-world robot deployment—ensuring accurate localization even when the environment is not static. Her approach combines visual, inertial, and semantic data, pushing the boundaries of how robots perceive and navigate complex indoor spaces. For students and researchers in robotics and computer vision, Lin’s work offers a practical pathway toward more resilient autonomous systems, demonstrating that robust perception is key to unlocking the full potential of mobile service robots in everyday environments.
Research Focus
Key Achievements
Top Papers
- 1