Affiliation:
1. Department of Computer and Information Science, University of Konstanz, 78457 Konstanz, Germany
Abstract
Human handwriting is an everyday task performed regularly by most people. In the domain of robotic painting, multiple calligraphy machines exist which were built to replicate some aspects of human artistic writing; however, most projects are limited to a specific style of handwriting, often Chinese calligraphy. We propose a two-stage pipeline that allows industrial robots to write text in arbitrary typefaces and scripts using paintbrushes. In the first stage, we extract a set of strokes from character glyphs which are similar to how humans choose strokes during writing. In the second stage, we generate corresponding brush trajectories by applying a brush model to the extracted strokes. Our brush model computes the required brush pressure to achieve the given stroke width while also accounting for brush lag. We also present a method to automatically measure the parameters needed to predict brush lag by painting and recording calibration patterns. Our method generates trajectories for text in any given typeface, which, when executed by a robotic arm, results in legible written text. We can render most writing systems, excluding emoji and ligatures, in which arbitrary texts can be specified to write.
Subject
Artificial Intelligence,Control and Optimization,Mechanical Engineering
Reference27 articles.
1. Lloyd-Davies, V. (2019). Sumi-e Painting, Walter Foster Publishing.
2. Gülzow, J.M., Paetzold, P., and Deussen, O. (2020). Recent Developments Regarding Painting Robots for Research in Automatic Painting, Artificial Creativity, and Machine Learning. Appl. Sci., 10.
3. Gülzow, J.M., Grayver, L., and Deussen, O. (2018). Self-Improving Robotic Brushstroke Replication. Arts, 7.
4. Sun, Y., and Xu, Y. (2013, January 12–14). A calligraphy robot—Callibot: Design, analysis and applications. Proceedings of the 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, China.
5. Deussen, O., Lindemeier, T., Pirk, S., and Tautzenberger, M. (2012, January 4–6). Feedback-guided stroke placement for a painting machine. Proceedings of the Eighth Annual Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging, Aire-la-Ville, Switzerland.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献