From Knowable Magazine, December 4:
For this chore, the human touch still beats machines. But maybe not for long.
More than 60 years ago, Rosie the Robot made her TV debut in The Jetsons, seamlessly integrating herself into the Jetson household as she buzzed from room to room completing chores. Now, as reality catches up to science fiction and scientists work to develop modern-day Rosies, one of the most mundane tasks is proving to be a big challenge: folding laundry.
The ordinary-seeming act of picking up a T-shirt and folding it into a neat square requires a surprisingly complex understanding of how objects move in three dimensions. Our own ease in accomplishing such tasks comes from a learned understanding of how different fabrics will respond when folded, even if we haven’t folded them before, but robots struggle to apply what they learn to new situations that may differ from their training. As a result, current robots are slow and often perform poorly on even the simplest of folding tasks.
Now, however, newer approaches that adapt better to real-world scenarios may lay the groundwork for robots folding our laundry in the future.
A big challenge in teaching robots the skill is the infinity of ways that various fabrics can fold. Think about all the times you’ve tossed a T-shirt into the laundry basket and how it landed in a slightly different-shaped heap each time. It’s simple for people to pick up a shirt and quickly find a sleeve or collar to orient themselves, but every unique way a shirt crumples is a new challenge for robots, which are often trained on images of unwrinkled clothing lying flat on a surface, with all features visible.
“It’s not the fabric itself that is the challenge. It’s the amount of variations that can be created by the way fabric can be crumpled, and all the different kinds of clothing items that exist,” says David Held, a robotics researcher at Carnegie Mellon University in Pittsburgh.
That challenge is easier for people, because we are sensory sponges. Our eyes and hands provide a tremendous amount of information about the world through a lifetime of manipulating three-dimensional objects. Another result of all that learning is that simply looking at a piece of fabric gives us an intuition of how heavy or stretchy it is, and how it would best be folded. It’s clear to us that denim doesn’t fold like silk, for example, but robots don’t automatically understand that more force is required to lift and fold a pair of jeans than a delicate blouse and instead need to interact with the object before determining a folding plan....
....MUCH MORE
It's good to see the Carnegie Mellon mention. From the intro to 2016's "Interview: Manuela Veloso Head of Machine Learning, Carnegie Mellon University", reprised in November 27's "The self-driving taxi revolution begins at last":
Speaking of CMU:
May 2015 - Big Money: Uber Guts Carnegie Mellon Robotics Lab To Hire Autonomous Car Developers
June 2015 - "Uber Is Stealing Scientists, But Only So It Can Lay Off Drivers"
November 2016 - the introduction to "Interview: Manuela Veloso Head of Machine Learning, Carnegie Mellon University":
Our readers probably know Carnegie Mellon more for the top-ranked financial engineering program (Master of Science in Computational Finance) but artificial intelligence was pretty much invented at CMU by Herbert Simon and Allen Newell. Simon received the Nobel in Economics but it actually could have been for any of four or five subjects, he was quite the polymath.
Newell had to settle for the Turing award (along with Simon) from the Association for Computing Machinery, probably the root'in-tootin high-falootinest tchotchke in the computer biz.
The Association for the Advancement of Artificial Intelligence along with the ACM subsequently named an award in Newell's honor. Ditto for CMU.
The University's machine learning department was the first in the world to offer a doctorate and as far as I know is still the largest.
A department, for one branch of AI.
Carnegie-Mellon used to have a world class robotics Institute but Uber gutted it with a combination of cash and stock options leaving a Dean and a couple robots to rebuild.
One of the robots is said to be in advanced negotiations with the Ube-sters....
