Danling Lu

Papers

Total Citations

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About

Danling Lu is a leading researcher in human-robot interaction and intelligent gesture recognition systems. Her most-cited work, "Gesture recognition using data glove: An extreme learning machine method" (2016, 48 citations), pioneered the application of extreme learning machines for real-time, accurate hand gesture interpretation from data glove inputs. This contribution directly addresses the critical challenge of creating natural, intuitive interfaces for human-robot collaboration. Lu's research focuses on bridging the gap between human movement analysis and machine learning, particularly in modeling and recognizing complex hand gestures that serve as a fundamental mode of communication in HRI. By demonstrating that extreme learning machines can efficiently process high-dimensional gesture data, her work has enabled faster and more robust recognition systems compared to traditional neural network approaches. This innovation has significant implications for assistive technologies, virtual reality, and industrial robotics. Lu's contributions continue to influence the development of intelligent, responsive systems that understand human intent through natural motion, making her a key figure in advancing the field of gesture-based interaction.