Implementation and Evaluation of Intra-Hug Gestures During Dialogue for a Huggable Robot
Takuto Akiyoshi, Hidenobu Sumioka, Junya Nakanishi, Hirokazu Kato, Masahiro Shiomi
Abstract
Hugging provides psychological benefits and is common in supportive dialogue, leading to probabilistic models for a robot's intra-hug gestures (e.g., patting, rubbing). However, the psychological effects of this human-derived model have not been adequately verified. In this study, we aimed to clarify the psychological effects by implementing a model and a dialogue scenario for organizing user worries and goals in the huggable robot. We experimentally evaluated the effectiveness of the model-based system by comparing it with a system that performs random gestures according to uniform distributions without human characteristics. The results showed that participants who used the system with the model perceived the robot as significantly easier to use, felt that the robot was friendlier, and rated the overall goodness of the interaction session higher. Additionally, the model demonstrated a significant reduction in negative user comments regarding the frequency of gestures. Our quantitative and qualitative findings will help design interactions with huggable robots for mental health support.
BibTeX
@inproceedings{ral2026_implementationan,
title = {Implementation and Evaluation of Intra-Hug Gestures During Dialogue for a Huggable Robot},
author = {Takuto Akiyoshi and Hidenobu Sumioka and Junya Nakanishi and Hirokazu Kato and Masahiro Shiomi},
booktitle = {RA-L 2026},
year = {2026}
}