Shao‐Wen Yang
Papers
8
Total Citations
234
H-Index
8
About
Shao‐Wen Yang has made pioneering contributions to autonomous robotics, particularly in robust perception and navigation in complex, dynamic environments. His research focuses on solving fundamental challenges in LIDAR sensing, egomotion estimation, and simultaneous localization and mapping (SLAM). Yang is best known for his groundbreaking work on laser scanner failure on mirrors and windows—a critical yet underexplored problem—with two highly cited papers (each with 53 citations) that characterize and address sensing failures caused by reflective surfaces. He also developed innovative RANSAC-based algorithms for simultaneous registration, segmentation, and moving object detection, enabling robots to maintain robust egomotion estimation even in crowded urban scenes. His proposal of "feasibility grids" advanced mapping in dynamic environments by representing both static and moving elements. Yang's contributions have accumulated over 200 citations, and his annotated laser dataset for urban navigation remains a valuable resource for the robotics community. Through his work, Yang has significantly improved the reliability of autonomous systems operating in real-world, unpredictable settings.
Research Focus
Key Achievements
Top Papers
- 1Dealing with laser scanner failure: Mirrors and windows53 citations · 2008
- 2On Solving Mirror Reflection in LIDAR Sensing53 citations · 2010
- 3RANSAC matching: Simultaneous registration and segmentation38 citations · 2010
- 4Simultaneous egomotion estimation, segmentation, and moving object detection26 citations · 2011
- 5Feasibility grids for localization and mapping in crowded urban scenes23 citations · 2011
- 6
- 7The annotated laser data set for navigation in urban areas13 citations · 2011
- 8Interacting Object Tracking in Crowded Urban Areas11 citations · 2007