Generating Art using Robotics and AI: What is out there? (2012)

*** Access the full report here.

     Acess the introduction post here***

One of the first uses of randomization in arts is commonly attributed to Wolfgang Amadeus Mozart, in the field of music. He wrote the measures and instructions for a musical composition dice game, where pre-written measures of music were chosen according to a mapping between these and the results of throwing die; these were pasted together afterwards to create a Minuet. [1]

However, it was only in the 20th century that randomization in arts became more popular. John Cage’s work named Music of Changes in 1951 is often considered the first piece to be largely produced through random methods, where he used I Ching, a Chinese classic text commonly used as a divination system. He would “ask” the book questions about various aspects of the composition at hand and use the answers to compose.

In visual arts, it was Ellsworth Kelly, in 1957, who first featured generative methods in his pieces by using chance operations to assign colors in a grid, or colourful pictures and cheap materials cut into strips or squares to produce collages.

Kelly

Ellsworth Kelly, Spectrum Colors Arranged by Chance V, 1951

Other artists, namely, Alfred Jensen and Carl Andre, traditionally abstract artists also contributed to the generative art movement during the 20th century.

However, it was with Frieder Nake, a mathematician, that computer art became more well defined. He began to write computer programs to generate drawings. He used Zuze Z64 Graphomat, a digital plotter from 1961 developed by computer pioneer Konrad Zuse, to do drawings as of 1963. [2]

In 1973, the software AARON was born in University of Stanford developed by artist Harold Cohen and it is now a project that has been ongoing for many decades. AARON was one of the first machines to be made with the intention to programme a creative agent that produces art and collaborates with its creator. However, despite being an autonomous generator of drawings, it cannot learn new styles nor objects. Each new functionality and style has to be hand-coded. [3] For instance, when generating the drawing of a person, it goes back to memory and finds the components needed to generate a person (e.g. arm, torso, etc.), however, the randomness is introduced to decide the position of each component, for instance, at what angle the elbow is going to be at. \cite{aaron}

tn1k_In-Zanas-Room

AARON, In Zana’s Room, 2013

In 2006, in the Computational Creativity Research Group at Imperial College London the Painting Fool was born. The objective is to create a software that will be taken seriously as a creative agent.

Shortly after, in 2009, eDavid was started. This is a project from University of Konstanz, where researchers are creating a robot that physically paints.

eDavid project page

In 2012, Vangobot was built as a collaboration between an artist and a programmer. It’s a robot that given an image and instructions paints on a canvas, being able to accomplish different styles. [4] BNJMN was also created in 2012, as a project from the Basel Academy of Art and Design, and it is a “mobile sensory image production mechanism” [5]. It roams in search of paper and produces abstract art.

BNJMN

References:

[1] http://sunsite.univie.ac.at/Mozart/dice/

[2] R. Bowlin (2010), Z64 Graphomat and Frieder Nake. Available: http://issuu.com/rhondabowlin/docs/rbowlin_artreview01

[3] P. McCorduck, Aarons Code, W.H.Freeman & Co Ltd, 1991

[4] L. Kelly, D. Marx, (2012), The vangobot project, Available: http://vangobot.com

[5] http://web.fhnw.ch/hgk/projekte/interaktion/?/projects/picmac/bnjm/

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