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Self-Improving Robotic Brushstroke Replication

Fachbereich Informatik und Informationswissenschaft, Universität Konstanz, 78464 Konstanz, Germany
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Received: 28 September 2018 / Revised: 8 November 2018 / Accepted: 10 November 2018 / Published: 21 November 2018
(This article belongs to the Special Issue The Machine as Artist (for the 21st Century))
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Abstract

Painting robots, like e-David, are currently unable to create precise strokes in their paintings. We present a method to analyse given brushstrokes and extract their trajectory and width using a brush behaviour model and photographs of strokes painted by humans. Within the process, the robot experiments autonomously with different brush trajectories to improve the reproduction results, which are precise within a few millimetres for strokes up to 100 millimetres length. The method can be generalised to other robotic tasks with imprecise tools and visible results, like polishing or milling. View Full-Text
Keywords: robotics; painting; art; generative method; brush robotics; painting; art; generative method; brush
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Gülzow, J.M.; Grayver, L.; Deussen, O. Self-Improving Robotic Brushstroke Replication. Arts 2018, 7, 84.

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