In the Everyday Robots world, conquering a mundane task, such as crossing a cluttered room and opening a tricky door handle, is like winning the Super Bowl.
The café testing ground is one of dozens on the Google campus in Mountain View, California, where a small percentage of the company’s massive workforce has now returned to work. The project hopes to make robots useful, operating in the wild instead of controlled environments like factories. After years of development, Everyday Robots is finally sending its robots into the world—or at least out of the X headquarters building—to do actual work.
In an office he shares with a nonfunctional robot arm he built as a teenager, Brondmo explains that making an effective general-purpose robot became possible only with recent advances in machine learning. The engineers use machine learning to train the software to recognize objects and then run millions of simulations to compress weeks of testing into hours.
While executing Catie Cuan’s choreography, the robots respond to her movements and spontaneously generate a soundtrack from samples of the London Symphony Orchestra.Software engineer Benjie Holson, who grew up in a puppeteering family, appreciates a robot-swiped table.
Moravec was building a mobile robot. His goal was to place the robot on one side of a room and have it maneuver its way across the room, avoiding trash cans and desks. He approached the problem with standard assumptions. In order to negotiate its journey successfully, the machine would need a silicon “brain,” which would be the center of its cognition. In the memory of this brain, the robot would retain some sort of representation of the room.
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