A MultiModal Social Robot Toward Personalized Emotion Interaction

• URL: http://arxiv.org/abs/2110.05186v1
• Date: Fri, 8 Oct 2021 00:35:44 GMT
• Title: A MultiModal Social Robot Toward Personalized Emotion Interaction
• Authors: Baijun Xie and Chung Hyuk Park
• Abstract summary: This study demonstrates a multimodal human-robot interaction (HRI) framework with reinforcement learning to enhance the robotic interaction policy. The goal is to apply this framework in social scenarios that can let the robots generate a more natural and engaging HRI framework.
• Score: 1.2183405753834562
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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