arXiv · 2110.05186
A MultiModal Social Robot Toward Personalized Emotion Interaction
Abstract
Human emotions are expressed through multiple modalities, including verbal and non-verbal information. Moreover, the affective states of human users can be the indicator for the level of engagement and successful interaction, suitable for the robot to use as a rewarding factor to optimize robotic behaviors through interaction. This study demonstrates a multimodal human-robot interaction (HRI) framework with reinforcement learning to enhance the robotic interaction policy and personalize emotional interaction for a human user. The goal is to apply this framework in social scenarios that can let the robots generate a more natural and engaging HRI framework.
Explore related subjects
Keep this discovery
Baijun Xie, Chung Hyuk Park. 2021-10-08. A MultiModal Social Robot Toward Personalized Emotion Interaction. https://arxiv.org/abs/2110.05186
Cite the original work for its findings. Save a collection to share your selection of sources.