R. Romero

Papers

Total Citations

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About

R. Romero is a researcher in human-robot interaction, with a focus on developing intuitive, non-verbal communication systems between humans and social robots. Their primary research areas include gesture recognition, neural network-based interaction models, and assistive robotics. Romero’s most notable contribution is the development of a body gesture recognition system that enables natural, touch-free control of social robots. In their 2022 paper, they proposed a novel gesture-based language and created a custom dataset of human body gestures, training a neural network to accurately detect and interpret these movements. This work has garnered 4 citations and represents a foundational step toward more accessible and user-friendly robotic interfaces, particularly for individuals who may benefit from hands-free control. Romero’s research bridges computer vision, machine learning, and robotics, aiming to make social robots more responsive and adaptable in real-world environments. Their work is especially relevant for applications in healthcare, education, and domestic assistance, where natural interaction is key to user acceptance and effectiveness.