Understanding Intention of Others by Autonomous eye-tracking in Telepresence Avatar Robots

Abstract

COVID-19 and technological developments have increased opportunities for remote communication, including online meetings. This has led to a focus on “telepresence avatar robots”. The telepresence avatar robot takes an approach to support communication by generating a realistic sense of conversation by incorporating technologies such as camera motion and eye-contact with the speaker. However, these approaches do not provide intention estimation and do not achieve smooth communication Compared to local communication, it is difficult to achieve a sense of presence for the robot operator. In contrast, we implemented eye-tracking, which is behaviored unconsciously by humans, as an autonomous motion, and verified whether the robot operator performs intention estimation by these autonomous motion. Eye-tracking is an action in which one tracks the other’s gaze in a local conversation, and is performed unconsciously. The experimental results suggest that autonomous behavior generates gazing intention estimation, and that this approach may be a useful method for robot operators to obtain a sense of presence in the environment and to predict the behavior of others.