Brushstrokes in the Digital Age
Working With the e-David Painting Robot, University of Konstanz, Germany

Since October 2015 I have been in contact with Professor Oliver Deussen, who since 2010 has been developing the e-David, a robotic Drawing Apparatus for Vivid Interactive Display, at the University of Konstanz. Subsequent to our first encounter at MIT (Massachusetts Institute of Technology), I visited Prof. Deussen and his team at their lab in Constance, so that we could continue to discuss and re-evaluate the potential use of the robot from an artistic and creative perspective. This was followed by an invitation to return to Constance for a one-month working sojourn with the robot and the lab team. Over the course of June 2016, I also explored various approaches to integrating computer languages in the processes of painting and creative image-making.


Exhabition view; “Pinselstriche im digitalen Zeitalter Interdisziplinäre Forschung in Malerei & Robotik“ at the Halle 14, Februar 2017 Spinnerei Leipzig. Liat Grayver and e-David Team.  @ Marcus Nebe


Collaboration between the artist Liat Grayver,  Maor Rosenberg (curiosity lab Tel Aviv University ) and the e-David team, (university of Konstanz)

Saving, translating and repeating information in the painting process are features that computer- and robotic-based painting offers. These are used in my work to redefine, challenge and examine the structures and systems used in the process of making a painting by translating and assimilating logic from different disciplines into artistic expression. lately, I began investigating various methods for the transformation of information using the trajectories of organisms as a base to generate not only brushstrokes but even the entire architectonical structure of a painting.

The simple geometric form of a red rectangular creates a focal point for the viewer gaze, defining the space of action in which the architectural structure of the painting occurs.  The structure in this work was innately built using reinforcement learning algorithm, seeking for the optimal way to paint a red rectangular, raising the question--optimal in what way? 
The finished work contains a selection of 8 trajectory paintings. The paintings are a repetition of the task to paint a red rectangular according to pre-giving parameters, however, they are not a repetition of the execution itself, rather of different approaches: paintings done by the e-David robot using reinforcement learning algorithm,  trajectory of a fish movement which was following a VR  red dot that operated according  to the reinforcement learning algorithm of making a red rectangular and manually painted red rectangular executed by me, while  following  predefined parameters (action score) aligning with the algorithm given to the robot and the fish.



Upper left: red rectangular. Acrylic on canvas 40 x 60
upper right: simulation in Python of the learn algorithm to paint a rectangular
lower left: the e-David robot executing the painting
lower right: a fish following a V.R red dot that is painting a red rectangular