Developing a Vision and Contact Sensor-Based Android-to-Human Touch System That Enables Face and Arm Touch

Abstract

Mainstream use of AI has enabled human-like conversations with machines. Despite the perceived naturalness of these interactions, they are limited to 2D screens. Androids offer us an opportunity to explore the third dimension, touch, with a human-centered approach. In this work we developed and evaluated a system that lays some of the groundwork for future dialogues with these androids. While there have been robot-to-human studies that focus on behavior modification, handshakes, and hugs, many do not use human-looking androids, do not adapt to humans' positions, or do not explore face-touch. We demonstrate these shortcomings are surmountable with a system that can direct an android to touch along someone's arm or cheek. Our research goals were to create a system capable of subjective accuracy approaching human touch perception while maintaining participant rated naturalness scores no worse than those found with systems using nonadaptive android-to-human touch.To evaluate the system, 25 participants selected 30 touch locations while seated in front of a realistic, male-looking android. Coders found our mean contact-to-target arm accuracy to be 4.9 cm, which is only 4 mm over the 4.5 cm upper range for two-point discrimination tests of adults' arms. Participants rated the naturalness of our touches as 3.9/7, which is no worse than the 3.0/7 found in a previous work with a mechanically identical android that nonadaptively touched people's forearms. With both goals being met, we have demonstrated that natural adaptive touch with a realistic android, even for the sensitive face, is within reach of scientific studies.