We like to tell ourselves that learning by doing is the best strategy for improving our skills, but we seldom apply that philosophy to our robots; with certain exceptions, they're just supposed to know what to do from the start. Researchers at the Technical University of Darmstadt disagree and have developed algorithms proving that robot arms just need practice, practice, practice to learn complex activities. After some literal hand-holding with a human to understand the basics of a ping-pong swing, a TUD robot can gradually abstract those motions and return the ball in situations beyond the initial example. The technique is effective enough that the test arm took a mere hour of practice to successfully bounce back 88 percent of shots and compete with a human. That's certainly better than most of us fared after our first game. If all goes well, the science could lead to robots of all kinds that need only a small foundation of code to accomplish a lot. Just hope that the inevitable struggle between humans and robots isn't settled with a ping-pong match... it might end badly.
German robot arm learns ping-pong as it plays humans, might rival its masters
In this article: adaptation, algorithm, Darmstadt, darmstadt technical university, DarmstadtTechnicalUniversity, germany, improvisation, learning, minipost, ping pong, ping-pong, PingPong, Robopocalypse, robot arm, RobotArm, robots, table tennis, TableTennis, technical university of darmstadt, TechnicalUniversityOfDarmstadt
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