  Robotic drawing has become increasingly popular as an entertainment and
interactive tool. In this paper we present RoboCoDraw, a real-time
collaborative robot-based drawing system that draws stylized human face
sketches interactively in front of human users, by using the Generative
Adversarial Network (GAN)-based style transfer and a Random-Key Genetic
Algorithm (RKGA)-based path optimization. The proposed RoboCoDraw system takes
a real human face image as input, converts it to a stylized avatar, then draws
it with a robotic arm. A core component in this system is the Avatar-GAN
proposed by us, which generates a cartoon avatar face image from a real human
face. AvatarGAN is trained with unpaired face and avatar images only and can
generate avatar images of much better likeness with human face images in
comparison with the vanilla CycleGAN. After the avatar image is generated, it
is fed to a line extraction algorithm and converted to sketches. An RKGA-based
path optimization algorithm is applied to find a time-efficient robotic drawing
path to be executed by the robotic arm. We demonstrate the capability of
RoboCoDraw on various face images using a lightweight, safe collaborative robot
UR5.
