Mei Su

University of North Carolina at Charlotte

Papers

Total Citations

H-Index

About

Mei Su is a researcher whose work lies at the intersection of computer vision and robotics, with a particular focus on enabling reactive robotic systems to perceive and interact with their environment more intelligently. Her key contributions center on the automatic verification of principal contacts using vision, a method that allows robots to recognize unknown physical contacts between objects in real time. This work, published in 2002, addresses a critical challenge in robotics: providing high-level, online feedback that is robust to sensing uncertainties. By developing a vision-based approach to extract accurate contact information, Su has helped bridge the gap between raw sensor data and actionable robotic responses. Although her most-cited paper has garnered 5 citations, its impact lies in its foundational approach to contact recognition, a problem that remains relevant in modern robotic manipulation and autonomous systems. Su’s research exemplifies the integration of perception and action, offering a pathway for robots to operate more autonomously and adaptively in unstructured environments. Her work continues to inspire advances in reactive robotics and visual sensing.