Categories: AI/ML News

A deep learning model that generates nonverbal social behavior for robots

Researchers at the Electronics and Telecommunications Research Institute (ETRI) in Korea have recently developed a deep learning-based model that could help to produce engaging nonverbal social behaviors, such as hugging or shaking someone’s hand, in robots. Their model, presented in a paper pre-published on arXiv, can actively learn new context-appropriate social behaviors by observing interactions among humans.

EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning

This paper introduces a framework, called EMOTION, for generating expressive motion sequences in humanoid robots, enhancing their ability to engage in human-like non-verbal communication. Non-verbal cues such as facial expressions, gestures, and body movements play a crucial role in effective interpersonal interactions. Despite the advancements in robotic behaviors, existing methods…

January 25, 2025

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