Abstract
Artistic robotic painting automates the process of creating an artwork. This complex and challenging task includes several aspects: creating algorithms for rendering brushstrokes, reproducing the exact shape of a brushstroke, and developing the principles of mixing paints. This work contributes to the previously unsolved problem of accurately reproducing colors of brushstrokes by means of artistic paints. The main contributions of this paper include: the development of a novel 4-component data-driven mathematical model for artistic paint mixing; the design and implementation of a novel robot capable of accurately dosing and mixing acrylic paints thanks to the improved syringe pumps and the innovative paint mixer; the development of a novel pneumatic system for paint release with a build-in clogging detection mechanism. The capabilities of the designed robotic system are demonstrated by painting four artworks: replicas of Claude Monet’s and Arkady Rylov’s landscapes, a synthetic image generated using the StyleGAN2 neural network trained on Vincent van Gogh’s artistic heritage, and a synthetic image generated using the Midjourney neural network. The obtained results can be useful in various applications of computer creativity, as well as in artistic image replication and restoration, and also in colored 3D printing.
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Data Availability
Supplementary video in which the developed robot paints a synthetic image is available at https://youtu.be/NeZX1sPo7P4.
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Acknowledgements
The authors are grateful to T. Shpilevaya for the work dedicated to learning Style GAN 2 and generating the image in Fig. 14b.
Funding
This study is supported by Russian Science Foundation, project 22-79-00171.
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All authors contributed to the study’s conception and design. Artur Karimov and Denis Butusov conceptualized the proposed robotic system and were the supervisors of this project. Experimental robotic setup design and software development were performed by Artur Karimov and Ekaterina Kopets. The mathematical model of color mixing was developed by Artur Karimov and Sergey Leonov. The first draft of the manuscript was written by Artur Karimov, Denis Butusov, and Ekaterina Kopets. Ekaterina Kopets contributed to the 3D modeling and design of the planetary mixing device. Lorenzo Scalera is responsible for the experimentation part with image synthesis and drawing as well as for manuscript review and editing. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Karimov, A., Kopets, E., Leonov, S. et al. A Robot for Artistic Painting in Authentic Colors. J Intell Robot Syst 107, 34 (2023). https://doi.org/10.1007/s10846-023-01831-4
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DOI: https://doi.org/10.1007/s10846-023-01831-4