An interesting competition: RobotArt challenges people to make robotic art that may be exhibited and sold to the public, following these rules:
Paint/color must be applied with one or more physical brushes by a robotic system. Work done by an ink-jet-like matrix printer will not qualify.
You can use up to 8 different manually premixed colors of your choice during the entire painting process. These colors can be mixed together by the robotic system in an intermediate stage (e.g., on a palette).
For this year of the contest, we are flexible of what type of robot is used (arm, swarm, drone, roomba, etc)
Each team can submit up to six distinct art works in each of the two categories.
Team are open to everyone. Please read about prize payment information below.
While existing artwork (e.g., Mona Lisa) can be used as a basis of the final submission, a photo of the existing artwork must be uploaded and referenced.
Incorporating machine-learning technology, CloudPainter was able to paint evocative portraits with varying degrees of abstraction. The source code and 3d models for CloudPainter are available online, and its creator has written about and given talks on his philosophy and methodology.
2nd Place – $25,000 – PIX18 / Creative Machines Lab – Columbia University (USA)
The Columbia team, coming off of their 2017 win, continued with a collection of impressionistic artwork showing a high level of skill with brushstrokes.
3rd Place – $10,000 – CMIT ReART – Kasetsart University (Thailand)
Artists program this robot brushstroke by stroke, using a haptic recording system that generates volumes of data about the position of the brush and the forces being exerted. When re-played, reART will generate a perfect reproduction of the original strokes. Haptic recording and playback allows for remarkably high-quality ink brush drawings.
What kind of robotic art to you make or want to make? Let us know in the comments below!
Adafruit has had paid day off for voting for our team for years, if you need help getting that going for your organization, let us know – we can share how and why we did this as well as the good results. Here are some resources for voting by mail, voting in person, and some NY resources for our NY based teams as well. If there are additional resources to add, please let us know – adafruit.com/vote
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