Authors: Bosong Ding, Murat Kirtay, Giacomo Spigler
Abstract: Head movements are crucial for social human-human interaction. They can
transmit important cues (e.g., joint attention, speaker detection) that cannot
be achieved with verbal interaction alone. This advantage also holds for
human-robot interaction. Even though modeling human motions through generative
AI models has become an active research area within robotics in recent years,
the use of these methods for producing head movements in human-robot
interaction remains underexplored. In this work, we employed a generative AI
pipeline to produce human-like head movements for a Nao humanoid robot. In
addition, we tested the system on a real-time active-speaker tracking task in a
group conversation setting. Overall, the results show that the Nao robot
successfully imitates human head movements in a natural manner while actively
tracking the speakers during the conversation. Code and data from this study
are available at https://github.com/dingdingding60/Humanoids2024HRI
Source: http://arxiv.org/abs/2407.11915v1
