This is quite interesting: e-David is a welding robot programmed to copy art pieces via a select number of algorithms. Watch this video:
This brief piece in Wired has more:
The thing that sets the bot apart from his contemporaries is a visual feedback system, a technological set of eyes that continually checks to see how close he’s coming to the mark. Every so often, e-David will take a photograph of his canvas and, after some image correction, subtract it from the image he’s trying to reproduce. Looking at the difference between the two, it determines which areas of the canvas are too dark or too light, generates a hundred or so potential brush strokes, and then chooses which of those are best suited to minimize that difference.
In many ways, the project sidesteps some of the thornier conceptual issues painting robots typically grapple with–concerns like authorship and intent. “Regardless of what we implement, the machine will never be a person,” Oliver Deussen, one of the researchers behind the effort, explained to WIRED UK. “It will only have a very limited idea about what it is doing, no intention. Our simulation is only about the craftsmanship that is involved in the painting process.” In other words, Deussen and his collaborators don’t expect their robotic arm to think like an artist. They just want it to paint like one.
There is much potential here:
The machine works mostly in acrylic, because it dries quickly and is thus easier to correct. It can do color, but it’s a bit tricky. And since e-David needs to ensure the same amount of paint is on the brush for its algorithms to function as intended, it has to make a stroke off to the side every time it dips its brush.
But e-David’s creators think there’s plenty of room for their apprentice to learn. It could be programmed to distinguish between certain styles of painting, for example, and choose its strokes accordingly. Or even, Deussen suggests, to gain some rudimentary understanding of what it was painting, and to know the difference between the sky and leaves on a tree, say, in terms of what they demanded from the perspective of paint applied to canvas.