Humans are able to convey different messages using only touch. Equipping robots with the ability to understand social touch adds another modality in which humans and robots can communicate. In this paper, we present a social gesture recognition system using a fabric-based, large-scale tactile sensor placed onto the arms of a humanoid robot. We built a social gesture dataset using multiple participants and extracted temporal features for classification. By collecting tactile data on a humanoid robot, our system provides insights into human-robot social touch, and displays that the use of fabric based sensors could be a potential way of advancing the development of spHRI systems for more natural and effective communication.
View on arXiv@article{crowder2025_2503.03234,
title={ Social Gesture Recognition in spHRI: Leveraging Fabric-Based Tactile Sensing on Humanoid Robots },
author={ Dakarai Crowder and Kojo Vandyck and Xiping Sun and James McCann and Wenzhen Yuan },
journal={arXiv preprint arXiv:2503.03234},
year={ 2025 }
}