Qiulan Huang
Papers
2
Total Citations
7
H-Index
2
About
Qiulan Huang is a leading researcher in human-robot interaction, with a focus on motion retargeting and natural language understanding for robotic systems. Her work addresses critical challenges in enabling robots to fluidly and safely mimic human movements, even when kinematic configurations differ significantly. In her 2024 paper on frame-by-frame motion retargeting, Huang introduced novel methods for self-collision avoidance, allowing robots to generalize from diverse human demonstrations—a breakthrough for deploying robots in unstructured environments. This work has garnered 5 citations, reflecting its immediate impact on the field. More recently, in 2025, Huang advanced referring expression comprehension in semi-structured human-robot interaction, bridging the gap between natural language commands and robotic action. This research enhances robots' ability to interpret ambiguous references, making human-robot collaboration more intuitive. Huang's contributions are pivotal for developing adaptable, safe, and communicative robots, with applications ranging from manufacturing to assistive technology. Her innovative approaches to motion and language integration continue to shape the future of interactive robotics.
Research Focus
Key Achievements
Top Papers
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- 2