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Helping Robots Learn Quickly in New Environments


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RoboCLIP dramatically reduces how much data is needed to train robots.

Credit: iStock

An algorithm developed by computer scientists at the University of Southern California (USC) reduces the amount of data necessary to train robots and enable them to perform tasks after a single video demonstration or language description.

The RoboCLIP algorithm performed two to three times better than other imitation learning methods after one video or textual demonstration of a task.

RoboCLIP trains robots using video-language models (VLMs), which are pretrained on large numbers of video and textual demonstrations.

From USC Viterbi School of Engineering
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Abstracts Copyright © 2023 SmithBucklin, Washington, D.C., USA


 

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