Reinforcement Learning Based 3-D Surface Calligraphy Robot

We present a robotic calligraphy system designed for writing on complex curved surfaces, addressing the growing interest in applying robotic techniques to irregular substrates. Our system integrates a six-axis industrial robotic arm and a depth camera, enabling it to reproduce 2D target calligraphy...

Full description

Saved in:
Bibliographic Details
Published inInternational Conference on Control, Automation and Robotics : proceedings pp. 13 - 19
Main Authors Ye, Jiawei, Yu, Yanzhao, Wang, Xueqian
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.04.2025
Subjects
Calligraphy
Motion Planning
PPO
Reinforcement learning
Robot kinematics
Robot vision systems
Robotic
Robots
Service robots
Substrates
Surface treatment
Three-dimensional displays
Training
Writing
Online AccessGet full text
ISSN2251-2454
DOI10.1109/ICCAR64901.2025.11073055

Cover

More Information
Summary:We present a robotic calligraphy system designed for writing on complex curved surfaces, addressing the growing interest in applying robotic techniques to irregular substrates. Our system integrates a six-axis industrial robotic arm and a depth camera, enabling it to reproduce 2D target calligraphy images onto various 3D surfaces. By framing the writing process as an interactive task between the robot and its environment, we incorporate a reinforcement learning agent to optimize the writing strategy, ensuring generalized, distortion-free calligraphy across diverse surfaces. We specifically designed a reward function suited to the curved surface writing task. For the essential 2D-to-3D mapping, we employ the Least Squares Conformal Maps (LSCM) algorithm to minimize distortion. Experimental results on multiple curved surfaces demonstrate that the system achieves aesthetically pleasing calligraphy, highlighting its potential for advanced robotic applications in art and design.
ISSN:2251-2454
DOI:10.1109/ICCAR64901.2025.11073055