Yuyang Shao

The University of Tokyo, Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yuyang Shao is a robotics researcher specializing in visual odometry, simultaneous localization and mapping (SLAM), and 3D reconstruction for autonomous systems. His work focuses on enabling unmanned robots to operate effectively in challenging environments, particularly for disaster response applications such as debris flow management. Shao’s major contributions include developing novel visual odometry methods—frame-to-frame (FTF-VO) and multi-frame (MF-VO)—that enhance mobile robot localization accuracy using stereo cameras. He also proposed an ARFM-based 3D reconstruction technique to improve structure from motion (SfM) mapping, addressing critical scale and slope estimation challenges for teleoperated robots in hazardous settings. While his most-cited papers have garnered modest citation counts (3 and 2 citations respectively), they represent foundational work in practical SLAM solutions for unmanned construction and auto-investigation. Shao’s research bridges the gap between theoretical computer vision and real-world robotic deployment, offering valuable insights for students and researchers interested in field robotics, disaster robotics, and 3D mapping technologies.