Watch a Robot Dog Learn How to Deftly Fend Off a Human | Science - WIRED

Kick over this robot and it’ll quickly right itself—not because someone told it how, but because it taught itself to overcome the embarrassment, summarizes Matt Simon, science journalist at WIRED.

Dog illustration on white steps
Photo: YANG ET AL., SCI ROBOT. 5, EABB2174 (2020)

Study hard enough, kids, and maybe one day you’ll grow up to be a professional robot fighter. A few years ago, Boston Dynamics set the standard for the field by having people wielding hockey sticks try to keep Spot the quadrupedal robot from opening a door. Previously, in 2015, the far-out federal research agency Darpa hosted a challenge in which it forced clumsy humanoid robots to embarrass themselves on an obstacle course way outside the machines’ league. (I once asked you, dear readers, to stop laughing at them, but have since changed my mind.) And now, behold: The makers of the Jueying robot dog have taught it a fascinating way to fend off a human antagonizer who kicks it over or pushes it with a stick.

A team of researchers from China’s Zhejiang University—where the Jueying’s hardware was also developed—and the University of Edinburgh didn’t teach the Jueying how to recover after an assault, so much as they let the robot figure it out. It’s a dramatic departure from how a hardware developer like Boston Dynamics goes about teaching a robot how to move, using decades of human experience to hard code, line by line, the way a robot is supposed to react to stimuli like, um, a person’s foot...

Once the eight algorithmic experts were trained up, they needed to learn to work together as a team. So the researchers combined them into an overarching network to act as a kind of coach or team captain. This allows the Jueying’s artificial brain to tap into the knowledge of each expert—how to run, or turn, or right itself. “The coach or the captain will tell who is doing what, or who should do work together, at which time,” says Li. “So all experts can collaborate together as a whole team, and this drastically improves the capability of skills.” For example, when the robot is falling down and needs to recover, the system can detect that movement and trigger the expert that handles balancing.

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Source: WIRED