High-Speed, High-Quality Robotic Portrait Drawing System

Abstract

Although robotic portrait drawing has been a recurring topic in robotics, most robotic portrait drawing systems have focused on either speed or quality of the drawing due to various technical difficulties in pursuing both goals. In this work, we propose a novel robotic portrait drawing system that uses advanced machine-learning techniques and a variable line width Chinese calligraphy pen to draw a high-quality portrait in a short time. Our approach first detects the human keypoints from the incoming video stream and extracts the dominant human face from the video, and then uses a CycleGAN based algorithm to convert the image style into a black-and-white line drawing. After a number of optimization steps, we use a 6-DOF robotic arm and a calligraphy pen to quickly draw the portrait. The system has been openly demonstrated to the general public at the RoboWorld 2022 exhibition, where the system has drawn portraits of more than 40 visitors with a satisfaction rate of 95%.