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Self-Improving Robotic Brushstroke Replication

Fachbereich Informatik und Informationswissenschaft, Universität Konstanz, 78464 Konstanz, Germany
Author to whom correspondence should be addressed.
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))
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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MDPI and ACS Style

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

AMA Style

Gülzow JM, Grayver L, Deussen O. Self-Improving Robotic Brushstroke Replication. Arts. 2018; 7(4):84.

Chicago/Turabian Style

Gülzow, Jörg M., Liat Grayver, and Oliver Deussen. 2018. "Self-Improving Robotic Brushstroke Replication" Arts 7, no. 4: 84.

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