Visible to the public Learning in Motion: Dynamic Interactions for Increased Trust in Human-Robot Interaction Games

TitleLearning in Motion: Dynamic Interactions for Increased Trust in Human-Robot Interaction Games
Publication TypeConference Paper
Year of Publication2020
AuthorsYe, S., Feigh, K., Howard, A.
Conference Name2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
Date Published Sept. 2020
PublisherIEEE
ISBN Number978-1-7281-6075-7
KeywordsCognition, cognitive science literature, computer games, dance motion, dynamic interactions, embodied cognition, Human Behavior, human factors, human perspective, human-robot interaction, human-robot interaction games trust, human-robot interactions, humanoid robot, Humanoid robots, pubcrawl, resilience, Resiliency, Robot Trust, social empathy
Abstract

Embodiment of actions and tasks has typically been analyzed from the robot's perspective where the robot's embodiment helps develop and maintain trust. However, we ask a similar question looking at the interaction from the human perspective. Embodied cognition has been shown in the cognitive science literature to produce increased social empathy and cooperation. To understand how human embodiment can help develop and increase trust in human-robot interactions, we created conducted a study where participants were tasked with memorizing greek letters associated with dance motions with the help of a humanoid robot. Participants either performed the dance motion or utilized a touch screen during the interaction. The results showed that participants' trust in the robot increased at a higher rate during human embodiment of motions as opposed to utilizing a touch screen device.

URLhttps://ieeexplore.ieee.org/document/9223437
DOI10.1109/RO-MAN47096.2020.9223437
Citation Keyye_learning_2020