Real-Time Imitation of Human Head Motions, Blinks and Emotions by Nao Robot: A Closed-Loop Approach
Journal:
arXiv
Published Date:
Apr 28, 2025
Abstract
This paper introduces a novel approach for enabling real-time imitation of
human head motion by a Nao robot, with a primary focus on elevating human-robot
interactions. By using the robust capabilities of the MediaPipe as a computer
vision library and the DeepFace as an emotion recognition library, this
research endeavors to capture the subtleties of human head motion, including
blink actions and emotional expressions, and seamlessly incorporate these
indicators into the robot's responses. The result is a comprehensive framework
which facilitates precise head imitation within human-robot interactions,
utilizing a closed-loop approach that involves gathering real-time feedback
from the robot's imitation performance. This feedback loop ensures a high
degree of accuracy in modeling head motion, as evidenced by an impressive R2
score of 96.3 for pitch and 98.9 for yaw. Notably, the proposed approach holds
promise in improving communication for children with autism, offering them a
valuable tool for more effective interaction. In essence, proposed work
explores the integration of real-time head imitation and real-time emotion
recognition to enhance human-robot interactions, with potential benefits for
individuals with unique communication needs.
