Research brings together humans, robots and generative AI to create art

Peter Schaldenbrand, a Ph.D. pupil within the Robotics Institute poses subsequent to CoFRIDA. Credit: Carnegie Mellon University

Researchers at Carnegie Mellon University’s Robotics Institute (RI) have developed a robotic system that interactively co-paints with folks. Collaborative FRIDA (CoFRIDA) can work with customers of any creative means, inviting collaboration to create artwork in the true world.

“It’s like the drawing equivalent of a writing prompt,” mentioned Jim McCann, an affiliate RI professor who runs the RI’s Textiles Lab. “If you’re stuck and you don’t know what to do, it can put something on the page for you. It can break the barrier of an empty page. It’s a really interesting way of enhancing human creativity.”

CoFRIDA builds on past work with FRIDA, a multilab collaboration within the College of Pc Science.

Named after the artist Frida Kahlo, FRIDA (Framework and Robotics Initiative for Creating Arts) can use a paintbrush or a Sharpie to create a portray from a human person’s textual content prompts or picture examples. The mission was based by Jean Oh, an affiliate analysis professor within the RI and head of the Bot Intelligence Group (BIG), collectively with McCann and Ph.D. pupil Peter Schaldenbrand.

To help a extra collaborative creative creation expertise, RI Ph.D. pupil Gaurav Parmar and Assistant Professor Jun-Yan Zhu joined the FRIDA crew to develop CoFRIDA. The brand new system permits customers to supply textual content inputs to explain what they wish to paint. They’ll additionally take part within the creation course of, taking turns portray straight on the canvas with the robotic till they’ve realized their creative imaginative and prescient.

“CoFRIDA requires a higher level of intelligence than the original FRIDA, which creates an artwork alone from start to completion,” Oh mentioned. “Co-painting is analogous to working with another person, constantly needing to guess what they want. CoFRIDA has to understand the human user’s high-level goals to make that user’s strokes meaningful toward the goal.”

Credit: Carnegie Mellon University

Co-painting is by its nature collaborative, and growing information that trains a robotic to collaborate is troublesome and time-consuming. To get round this complication, CoFRIDA makes use of self-supervised coaching information based mostly on FRIDA’s stroke simulator and planner.

The researchers created a self-supervised, fine-tuning dataset by having FRIDA simulate work that consisted of a sequence of brush strokes, from which some strokes could possibly be eliminated to provide examples of partial work.

The crew needed to decide find out how to take away components from drawings within the coaching information whereas leaving sufficient of the picture for CoFRIDA to acknowledge it. For instance, researchers took away particulars just like the rim of a wheel or home windows in a automobile however left the define of the automobile.

“We tried to simulate different states of the drawing process,” Zhu mentioned. “It’s easy to get to the final sketch, but it’s quite hard to imagine the intermediate stage of this process.”

Utilizing the dataset of partial and full work, the researchers fine-tuned a text-to-image mannequin, InstructPix2Pix, that enabled CoFRIDA so as to add brush strokes and work with present content material on the canvas. This method, which depends on information created utilizing CoFRIDA’s brush simulator, implies that producing a portray incorporates the robotic’s actual constraints, similar to its restricted set of instruments.

Exterior the lab, researchers hope CoFRIDA can train folks about robotics and increase creativity, encouraging individuals who might doubt their creative talents. CoFRIDA can even assist make customers’ visions come to life or take the art work in a complete new path.

“If you start from a very simple sketch, CoFRIDA takes the artwork in vastly different directions. If you ask for six different drawings, you’ll get six very different options,” Schaldenbrand mentioned.

“It’s nice to be able to make decisions at a high level because it makes me feel like an art director. The robot makes these low-level decisions of where to put the marker, but I get to decide what the overall thing will look like. I still feel in control of the creative process, and in a world where artists fear replacement by AI, CoFRIDA as an example of a robot designed to support human creativity is incredibly relevant.”

Researchers hope additional work can combine personalization into CoFRIDA, giving customers much more management over the model of the completed product.

The crew’s paper, “CoFRIDA: Self-Supervised Fine-Tuning for Human-Robot Co-Painting,” received the Finest Paper Award on Human Robotic Interplay on the 2024 IEEE Worldwide Convention on Robotics and Automation (ICRA) in Yokohama, Japan. An accompanying CoFRIDA demonstration was a finalist for the Finest Demo on the ICRA EXPO. The paper is available on the arXiv preprint server.

Extra info:
Peter Schaldenbrand et al, CoFRIDA: Self-Supervised Tremendous-Tuning for Human-Robotic Co-Portray, arXiv (2024). DOI: 10.48550/arxiv.2402.13442

Journal info:

Research brings collectively people, robots and generative AI to create artwork (2024, May 31)
retrieved 31 May 2024

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