Papers
6
Total Citations
91
H-Index
4
About
Xuefeng Liang is a researcher whose work bridges the critical intersection of human-robot interaction and intelligent sensing. His primary research areas include speech emotion recognition, robot manipulation, and multi-robot localization. Liang’s most significant contribution is his pioneering work on ambiguous speech emotion recognition, where he developed a multi-classifier interactive learning framework that addresses the inherent ambiguity in human emotional expression—a breakthrough that has garnered 57 citations. This work has profound implications for improving feedback efficiency in call centers, social robots, and healthcare applications. In the domain of robotics, Liang introduced the Coded Landmark for Ubiquitous Environment (CLUE), a visual marker system that simplifies robot manipulation using RT-middleware components. He also designed a large planar camera array for automated guided vehicle systems, dramatically extending surveillance scope and enabling precise multi-robot localization with high response speed. His development of a simulation framework for ubiquitous robots using RT-middleware further demonstrates his commitment to creating robust, distributed sensing environments. Through these contributions, Liang has established himself as a key figure in advancing intelligent, emotionally-aware robotic systems for real-world applications.
Research Focus
Key Achievements
Top Papers
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- 2Visual Mark for Robot Manipulation and Its RT-Middleware Component14 citations · 2008
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