Papers
2
Total Citations
8
H-Index
2
About
Yunqiang Pei is a rising researcher at the forefront of embodied AI and human-robot interaction (HRI), with a sharp focus on bridging the gap between natural language, 3D perception, and intuitive robotic control. His work centers on two critical challenges: enabling robots to understand complex spatial language through 3D visual grounding, and making human-robot collaboration more comfortable and efficient using Augmented Reality (AR). Pei’s most notable contribution is **ScanERU**, a pioneering framework for interactive 3D visual grounding that allows robots to link natural language descriptions to specific regions in a 3D point cloud scene—a fundamental capability for seamless human-robot dialogue. This work has already garnered 6 citations since its 2024 publication. Complementing this, his research on **Dynamic Dual-Layer Interaction Adjustment** tackles the practical discomfort of authoring tasks in AR-HRI, proposing adaptive systems that enhance user comfort and expressiveness. By addressing both the perceptual and ergonomic dimensions of interaction, Pei is laying the groundwork for more natural, trustworthy, and responsive robotic assistants. His emerging portfolio signals a dedicated trajectory toward making embodied AI not just smarter, but genuinely collaborative.
Research Focus
Key Achievements
Top Papers
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