UW Roboticists Learn to Teach Robots from Babies
December 2, 2015 | University of WashingtonEstimated reading time: 5 minutes
“If the human pushes an object to a new location, it may be easier and more reliable for a robot with a gripper to pick it up to move it there rather than push it,” said lead author Michael Jae-Yoon Chung, a UW doctoral student in computer science and engineering. “But that requires knowing what the goal is, which is a hard problem in robotics and which our paper tries to address.”
Though the initial experiments involved learning how to infer goals and imitate simple behaviors, the team plans to explore how such a model can help robots learn more complicated tasks.
“Babies learn through their own play and by watching others,” says Meltzoff, “and they are the best learners on the planet — why not design robots that learn as effortlessly as a child?”
The research was funded by the Office of Naval Research, National Science Foundation and Intel.
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