13 March 2012

Teach Your Robot Well

Within a decade, personal robots could become as common in U.S. homes as any other major appliance, and many if not most of these machines will be able to perform innumerable tasks not explicitly imagined by their manufacturers. This opens up a wider world of personal robotics, in which machines are doing anything their owners can program them to do—without actually being programmers. A new study by researchers in Georgia Tech’s Center for Robotics & Intelligent Machines (RIM), identified the types of questions a robot can ask during a learning interaction that are most likely to characterize a smooth and productive human-robot relationship.

These questions are about certain features of tasks, more so than labels of task components or real-time demonstrations of the task itself, and the researchers identified them not by studying robots, but by studying the everyday people who one day will be their masters. The study attempted to discover the role ‘active learning’ concepts play in human-robot interaction. In a nutshell, active learning refers to giving machine learners more control over the information they receive. Simon, a humanoid robot created in the lab of Georgia Tech’s School of Interactive Computing is well acquainted with active learning; researchers are programming him to learn new tasks by asking questions.

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