@inproceedings {pub6671pub6764,
	title = {Emotion Retargeting for Social Physical Human{\textendash}Robot Interaction: Real-Time Learning of Expressive Robot Behaviors via Full-Body Human Mapping},
	author = {Chao Wang AND Fan Zhang AND Michael Gienger},
	year = {2026},
	month = {June},
	abstract = {Expressive behavior is essential for robots to effectively convey emotional states during interactions with humans, particularly in social physical human{\textendash}robot interaction (spHRI) scenarios. We present a framework for collecting realistic and diverse robotic emotional expressions through expert demonstrations captured using a mixed reality (MR) headset. Our system enables experts to teleoperate both virtual and physical robots from a first-person perspective, capturing facial expressions, head movements, and upper-body gestures. These human behaviors are then retargeted to corresponding robotic components, including eyes, ears, neck, and arms.
Building on this dataset, we employ a flow-matching-based generative model that learns to produce coherent and diverse expressive behaviors in real time. The model responds dynamically to environmental stimuli, such as moving objects, while being explicitly conditioned on predefined emotional states.We demonstrate that our end-to-end pipeline{\textemdash}from immersive data collection to real-time behavior generation{\textemdash}provides an effective approach for synthesizing expressive robot behaviors, advancing the development of socially aware and emotionally expressive robots for spHRI.},
	publisher = {IEEE},
	booktitle = {IEEE ICRA 2026 Workshop Learning-HRI}
}