Robotic 'artist' Spray Can To Paint Giant Murals

Posted: Apr 11 2016, 7:17am CDT | by , in News | Latest Science News


Robotic 'artist' spray can to paint giant murals
Photo Credit: Getty Images

New York, April 11 (IANS) Scientists have invented a “smart” paint spray can that robotically reproduces photographs as giant murals.

The computerised technique which basically spray paints a photo is not likely to spawn a wave of giant graffiti but it can be used in digital fabrication, digital and visual arts, artistic stylisation and other applications, said the team from Dartmouth college and colleagues.

The system uses an ordinary paint spray can, tracks the can's position relative to the wall or canvas and recognises what image it "wants" to paint.

As the person waves the pre-programmed spray can around the canvas, the system automatically operates the spray on and off button to reproduce the specific image as a spray painting.

“We show that by combining computer graphics and computer vision techniques, we can bring such assistance technology to the physical world even for this very traditional painting medium, creating a somewhat unconventional form of digital fabrication,” said study co-author Wojciech Jarosz who worked as senior research scientist at Disney Research Zurich.

“We wanted to maintain the aesthetic aspects of physical spray painting and the tactile experience of holding and waving a physical spray can while enabling unskilled users to create a physical piece of art,” he added.

The prototype includes two webcams and QR-coded cubes for tracking and a small actuation device for the spray can 00 attached via a 3D-printed mount.

Paint commands are transmitted via radio directly connected to a servo-motor operating the spray nozzle.

Running on a nearby computer, the real-time algorithm determines the optimal amount of paint of the current colour to spray at the spray can's tracked location.

“The end result is that the painting reveals itself as the user waves the can around, without the user necessarily needing to know the image beforehand,” the team noted in a paper that appeared in the journal Computer & Graphics.

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