Modulating Multimodal Emotional and Social Perception of Huggable Robot Expressions Through Chest Haptics

Area of Science:

• Human-Robot Interaction
• Affective Computing
• Haptics

Background:

• Socially empathic human-robot interaction relies on emotional and social expression.
• The chest is a key interface for affective haptic and auditory cues in huggable robots.
• Existing chest haptic designs are limited, focusing on basic tactile parameters or heartbeat patterns.

Purpose of the Study:

• To explore richer multimodal expression using chest haptic patterns.
• To investigate the influence of chest haptic patterns on affective perception and social-emotional evaluation.
• To guide the development of huggable robots with enhanced emotional and empathic capabilities.

Main Methods:

• Implemented a 3x3 chest-mounted vibrotactile array on a huggable robot.
• Designed chest haptic patterns using path type and activation area as parameters.
• Conducted two experiments evaluating responses to emotional music and empathic speech with chest haptics.

Main Results:

• Chest haptic patterns modulated emotional ratings in response to music, with varied effects depending on the music.
• The inclusion of chest haptics generally improved social-emotional evaluations of empathic speech.
• Specific haptic patterns demonstrated more pronounced modulation effects in certain contexts.

Conclusions:

• Chest haptic patterns offer a promising avenue for multimodal social-emotional expression in human-robot interaction.
• The findings support the use of dynamic chest haptic patterns for richer affective communication.
• This research provides empirical evidence and design guidance for future empathic robotic systems.