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While roboticists have introduced increasingly sophisticated robotic systems over the past decades, most of the solutions introduced so far are pre-programmed and trained to tackle specific tasks. The ability to continuously teach robots new skills while interacting with them could be highly beneficial and could facilitate their widespread use.

Researchers at Arizona State University (ASU) recently developed a new computational approach that could allow users to continually train robots on new tasks via dialogue-based interactions. This approach, introduced in a paper posted to the arXiv preprint server, was initially used to teach a robotic manipulator how to successfully prepare a cold sandwich.

"Our goal is to contribute to the deployment of robots in people's homes that can learn to cook cold meals," Nakul Gopalan, supervising author for the paper, told Tech Xplore. "We want this from a user perspective where we understand what behaviors people need from a household robot.

"This user perspective has led us to using language and dialogue when communicating with robots. Unfortunately, these robots might not come knowing everything, like how to cook pasta for you."

The key objective of the recent work by Gopalan and his colleagues was to devise a method that would allow robots to rapidly acquire previously unknown skills or behaviors from human agents.

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