6 August, 2018
To train their machines to manipulate objects in the real world, they needed access to lots of houses—their own homes, and their friends’ homes, until they ran out of homes. So when their robot was all trained up, they put it to the test in the unfamiliar world of Airbnbs.
Before you ask: Yes, the homeowners knew who their robotic renters were. And yes, the robots—which look a lot like a Roomba with an arm attached—were very lovely guests. (They stayed for around a day and a half, accompanied by a few scientists testing them.) “I remember they were really excited and wanted to see how the robot does at different parts of the house,” says CMU roboticist Lerrel Pinto. “They told us that we were free to use the robot in other parts of the house.” The researchers did, by the way. “Also some were curious and checking out the robot and how it moved and asked if it can pick up trash from the floor for them.”
It couldn’t. But what the robot could do was show off how it had learned to manipulate novel objects the researchers brought along, from staplers to stuffed toys to spray bottles. These the researchers placed on various kinds of flooring, be it carpet or hardwood, which gave the robot varied backgrounds to work with.
You can teach machines to grasp in one of two ways, generally speaking: In a simulation, or with real-world practice. Simulations are good because they’re fast; you can get a digital model of a robot to test many hundreds of grips in the time it would take a pokey machine to move its elbow slightly, move its wrist slightly, and see what happens. Unfortunately, you can’t perfectly model the real world in digital: Physical tests are the only way to make sure that training truly matches up with real-world physics. (You can also do something called imitation learning, where you joystick a robot around and it learns how to move that way—lotta work, though.)
And the ultimate physical test takes robots outside the sterile environments constructed for lab tests and into the messy, disorderly lives of humans. “We need to take our robots into homes,” says Abhinav Gupta, a roboticist at CMU who helped develop the new system. “We need to collect lots of data of manipulation in a real setting where the floors can be different—sometimes it can be carpet, sometimes it can be tiled floor, sometimes it can be wooden floor.”